6303 Retrieval Jobs - Page 8

Job Title: Applied AI Engineer – LLMs, LangChain, Agentic Systems 📍 Location: Kochi (first 6 months) → Bangalore (long-term) 🕑 Experience: 2–3 years (must be hands-on) 📡 Mode: Full-time, on-site (hybrid possible after Kochi phase) 🧭 Reports To: AI Innovation Leader About the Role: We’re hiring a hands-on Applied AI Engineer to join a pioneering AI Innovation initiative at Geojit Financial Services, one of India’s most respected and long-standing financial services firms. As part of Geojit’s Vision 2030 strategy, we’re embedding AI across all layers of the business — from transforming customer experience to automating intelligence in operations, wealth, and capital market platforms. This role offers the unique opportunity to work directly with leadership, build real-world AI systems, and be part of the core team shaping the future of intelligent finance in India. What You’ll Work On: As part of the AI Innovation Center of Excellence (CoE), your responsibilities include: 🚀 AI Solution Development Build and deploy LLM-powered agents for real business use cases across customer service, research automation, internal knowledge retrieval, and document intelligence Design agentic AI workflows using LangChain — integrating memory, tools, retrievers, custom functions, and chaining logic Evaluate and integrate Text-to-SQL models that translate natural queries into live database queries Leverage AWS Bedrock and SageMaker pipelines for experimentation, deployment, and orchestration 📊 Data Engineering & EDA: Work with structured and semi-structured data (CSV, SQL, JSON, APIs) Perform Exploratory Data Analysis (EDA) using Plotly, Dash, or Streamlit for internal tools and decision support Assist in creating reusable tools, dashboards, or data layers to support ongoing experimentation 🛠️ Architecture & MLOps :Collaborate with the AI Lead and Infra teams to design scalable MLOps setup s Create or contribute to prompt optimization frameworks, RAG pipelines, evaluation frameworks, and agent monitoring tool s Integrate APIs, vector stores, document retrievers, and internal knowledge base s Required Skills :✅ 2–3 years hands-on experience with :LLMs and GenAI APIs – OpenAI, Cohere, Anthropic, etc . LangChain (must-have) – agents, tools, memory, multi-hop chains, and integration experienc e Agentic AI – experience designing task-based autonomous or semi-autonomous workflow s Text-to-SQL models – understanding of evaluation techniques and production concern s AWS ecosystem – especially SageMaker, Bedrock, Lambda, API Gatewa y Data wrangling & visualization – Pandas, SQL, Plotly/Dash/Streamli t Nice to have :Fintech domain exposur e Participation in AI/ML hackathons or open-source contribution s Familiarity with vector search, embeddings (FAISS, Weaviate, etc. ) Frontend integration knowledge for internal tools (basic Streamlit/Dash/Flask ) About the Project & Culture : You’ll be working in a startup-style team embedded inside a legacy enterprise—delivering quick iterations, visible impact, and cross-functional collaboration with leadership. The goal is to show business value in less than 100 days, and scale AI across :Capital Market s Wealth & Investment Advisor y Mutual Funds & Insurance Distributio n Internal Productivity System s About Geojit :Geojit Financial Services Ltd is a pioneer in India’s capital markets with a 38-year legacy, 1M+ clients, and presence across 500+ offices. With backing from BNP Paribas and KSIDC, Geojit has been a leader in digital innovation :India’s first online trading platform (2000 ) Early movers in mobile trading, Smartfolios, Funds Genie, and Portfolio Managemen t Now entering a new AI-led chapter under the leadership of Jayakrishnan Sasidharan (ex-Adobe, Wipro, TCS ) They are committed to delivering personalized, intelligent, and frictionless experiences to millions of investors — powered by AI, data, and design . Why Join Us ?Work on real GenAI deployments with measurable RO I Direct access to decision-makers, not just product manager s Be part of India’s next Fintech transformation stor y Hands-on exposure to enterprise-scale AI architectur e Build something that millions will use — not just a lab prototyp e 📩 How to Appl ySend your resume via WhatsApp (preferred) or email :📱 WhatsApp: +91 900800002 0📧 Email: sureshaisales@gmail.co m📝 Subject: “Applied AI Role – Geojit ”

Applied Machine Learning Scientist – Voice AI, NLP & GenAI Applications Location : Sector 63, Gurugram, Haryana – 100% In-Office Working Days : Monday to Friday, with 2nd and 4th Saturdays off Working Hours : 10:30 AM – 8:00 PM Experience : 3–7 years in applied ML, with at least 2 years focused on voice, NLP, or GenAI deployments Function : AI/ML Research & Engineering | Conversational Intelligence | Real-time Model Deployment Apply : careers@darwix.ai Subject Line : “Application – Applied ML Scientist – [Your Name]” About Darwix AI Darwix AI is a GenAI-powered platform transforming how enterprise sales, support, and credit teams engage with customers. Our proprietary AI stack ingests data across calls, chat, email, and CCTV streams to generate: Real-time nudges for agents and reps Conversational analytics and scoring to drive performance CCTV-based behavior insights to boost in-store conversion We’re live across leading enterprises in India and MENA, including IndiaMart, Wakefit, Emaar, GIVA, Bank Dofar , and others. We’re backed by top-tier operators and venture investors and scaling rapidly across multiple verticals and geographies. Role Overview We are looking for a hands-on, impact-driven Applied Machine Learning Scientist to build, optimize, and productionize AI models across ASR, NLP, and LLM-driven intelligence layers . This is a core role in our AI/ML team where you’ll be responsible for building the foundational ML capabilities that drive our real-time sales intelligence platform. You will work on large-scale multilingual voice-to-text pipelines, transformer-based intent detection, and retrieval-augmented generation systems used in live enterprise deployments. Key ResponsibilitiesVoice-to-Text (ASR) Engineering Deploy and fine-tune ASR models such as WhisperX, wav2vec 2.0, or DeepSpeech for Indian and GCC languages Integrate diarization and punctuation recovery pipelines Benchmark and improve transcription accuracy across noisy call environments Optimize ASR latency for real-time and batch processing modes NLP & Conversational Intelligence Train and deploy NLP models for sentence classification, intent tagging, sentiment, emotion, and behavioral scoring Build call scoring logic aligned to domain-specific taxonomies (sales pitch, empathy, CTA, etc.) Fine-tune transformers (BERT, RoBERTa, etc.) for multilingual performance Contribute to real-time inference APIs for NLP outputs in live dashboards GenAI & LLM Systems Design and test GenAI prompts for summarization, coaching, and feedback generation Integrate retrieval-augmented generation (RAG) using OpenAI, HuggingFace, or open-source LLMs Collaborate with product and engineering teams to deliver LLM-based features with measurable accuracy and latency metrics Implement prompt tuning, caching, and fallback strategies to ensure system reliability Experimentation & Deployment Own model lifecycle: data preparation, training, evaluation, deployment, monitoring Build reproducible training pipelines using MLflow, DVC, or similar tools Write efficient, well-structured, production-ready code for inference APIs Document experiments and share insights with cross-functional teams Required Qualifications Bachelor’s or Master’s degree in Computer Science, AI, Data Science, or related fields 3–7 years experience applying ML in production, including NLP and/or speech Experience with transformer-based architectures for text or audio (e.g., BERT, Wav2Vec, Whisper) Strong Python skills with experience in PyTorch or TensorFlow Experience with REST APIs, model packaging (FastAPI, Flask, etc.), and containerization (Docker) Familiarity with audio pre-processing, signal enhancement, or feature extraction (MFCC, spectrograms) Knowledge of MLOps tools for experiment tracking, monitoring, and reproducibility Ability to work collaboratively in a fast-paced startup environment Preferred Skills Prior experience working with multilingual datasets (Hindi, Arabic, Tamil, etc.) Knowledge of diarization and speaker separation algorithms Experience with LLM APIs (OpenAI, Cohere, Mistral, LLaMA) and RAG pipelines Familiarity with inference optimization techniques (quantization, ONNX, TorchScript) Contribution to open-source ASR or NLP projects Working knowledge of AWS/GCP/Azure cloud platforms What Success Looks Like Transcription accuracy improvement ≥ 85% across core languages NLP pipelines used in ≥ 80% of Darwix AI’s daily analyzed calls 3–5 LLM-driven product features delivered in the first year Inference latency reduced by 30–50% through model and infra optimization AI features embedded across all Tier 1 customer accounts within 12 months Life at Darwix AI You will be working in a high-velocity product organization where AI is core to our value proposition. You’ll collaborate directly with the founding team and cross-functional leads, have access to enterprise datasets, and work on ML systems that impact large-scale, real-time operations. We value rigor, ownership, and speed. Model ideas become experiments in days, and successful experiments become deployed product features in weeks. Compensation & Perks Competitive fixed salary based on experience Quarterly/Annual performance-linked bonuses ESOP eligibility post 12 months Compute credits and model experimentation environment Health insurance, mental wellness stipend Premium tools and GPU access for model development Learning wallet for certifications, courses, and AI research access Career Path Year 1: Deliver production-grade ASR/NLP/LLM systems for high-usage product modules Year 2: Transition into Senior Applied Scientist or Tech Lead for conversation intelligence Year 3: Grow into Head of Applied AI or Architect-level roles across vertical product lines How to Apply Email the following to careers@darwix.ai : Updated resume (PDF) A short write-up (200 words max): “How would you design and optimize a multilingual voice-to-text and NLP pipeline for noisy call center data in Hindi and English?” Optional: GitHub or portfolio links demonstrating your work Subject Line : “Application – Applied Machine Learning Scientist – [Your Name]”

Head of AI & ML Platforms Focus : Voice AI, NLP, Conversation Intelligence for Omnichannel Enterprise Sales Location : Sector 63, Gurugram, Haryana — Full-time, 100% In-Office Work Hours : 10:30 AM – 8:00 PM, Monday to Friday (2nd and 4th Saturdays off) Experience Required : 8–15 years in AI/ML, with 3+ years leading teams in voice, NLP, or conversation platforms Apply : careers@darwix.ai Subject Line : “Application – Head of AI & ML Platforms – [Your Name]” About Darwix AI Darwix AI is a GenAI-powered platform for enterprise revenue teams across sales, support, credit, and retail. Our proprietary AI stack ingests multimodal inputs—voice calls, chat logs, emails, and CCTV streams—and delivers contextual nudges, conversation scoring, and performance analytics in real time. Our suite of products includes: Transform+ : Real-time conversational intelligence for contact centers and field sales Sherpa.ai : A multilingual GenAI assistant that provides in-the-moment coaching, summaries, and objection handling support Store Intel : A computer vision solution that transforms CCTV feeds into actionable insights for physical retail spaces Darwix AI is trusted by large enterprises such as IndiaMart, Wakefit, Emaar, GIVA, Bank Dofar, and Sobha Realty , and is backed by leading institutional and operator investors. We are expanding rapidly across India, the Middle East, and Southeast Asia. Role Overview We are seeking a highly experienced and technically strong Head of AI & ML Platforms to architect and lead the end-to-end AI systems powering our voice intelligence, NLP, and GenAI solutions. This is a leadership role that blends research depth with applied engineering execution. The ideal candidate will have deep experience in building and deploying voice-to-text pipelines, multilingual NLP systems, and production-grade inference workflows. The individual will be responsible for model design, accuracy benchmarking, latency optimization, infrastructure orchestration, and integration across our product suite. This is a critical leadership role with direct influence over product velocity, enterprise client outcomes, and future platform scalability. Key ResponsibilitiesVoice-to-Text (ASR) Architecture Lead the design and optimization of large-scale automatic speech recognition (ASR) pipelines using open-source and commercial frameworks (e.g., WhisperX, Deepgram, AWS Transcribe) Enhance speaker diarization, custom vocabulary accuracy, and latency performance for real-time streaming scenarios Build fallback ASR workflows for offline and batch mode processing Implement multilingual and domain-specific tuning, especially for Indian and GCC languages Natural Language Processing and Conversation Analysis Build NLP models for conversation segmentation, intent detection, tone/sentiment analysis, and call scoring Implement multilingual support (Hindi, Arabic, Tamil, etc.) with fallback strategies for mixed-language and dialectal inputs Develop robust algorithms for real-time classification of sales behaviors (e.g., probing, pitching, objection handling) Train and fine-tune transformer-based models (e.g., BERT, RoBERTa, DeBERTa) and sentence embedding models for text analytics GenAI and LLM Integration Design modular GenAI pipelines for nudging, summarization, and response generation using tools like LangChain, LlamaIndex, and OpenAI APIs Implement retrieval-augmented generation (RAG) architectures for contextual, accurate, and hallucination-resistant outputs Build prompt orchestration frameworks that support real-time sales coaching across channels Ensure safety, reliability, and performance of LLM-driven outputs across use cases Infrastructure and Deployment Lead the development of scalable, secure, and low-latency AI services deployed via FastAPI, TorchServe, or similar frameworks Oversee model versioning, monitoring, and retraining workflows using MLflow, DVC, or other MLOps tools Build hybrid inference systems for batch, real-time, and edge scenarios depending on product usage Optimize inference pipelines for GPU/CPU balance, resource scheduling, and runtime efficiency Team Leadership and Cross-functional Collaboration Recruit, manage, and mentor a team of machine learning engineers and research scientists Collaborate closely with Product, Engineering, and Customer Success to translate product requirements into AI features Own AI roadmap planning, sprint delivery, and KPI measurement Serve as the subject-matter expert for AI-related client discussions, sales demos, and enterprise implementation roadmaps Required Qualifications 8+ years of experience in AI/ML with a minimum of 3 years in voice AI, NLP, or conversational platforms Proven experience delivering production-grade ASR or NLP systems at scale Deep familiarity with Python, PyTorch, HuggingFace, FastAPI, and containerized environments (Docker/Kubernetes) Expertise in fine-tuning LLMs and building multi-language, multi-modal intelligence stacks Demonstrated experience with tools such as WhisperX, Deepgram, Azure Speech, LangChain, MLflow, or Triton Inference Server Experience deploying real-time or near real-time inference models at enterprise scale Strong architectural thinking with the ability to design modular, reusable, and scalable ML services Track record of building and leading high-performing ML teams Preferred Skills Background in telecom, contact center AI, conversational analytics, or field sales optimization Familiarity with GPU deployment, model quantization, and inference optimization Experience with low-resource languages and multilingual data augmentation Understanding of sales enablement workflows and domain-specific ontology development Experience integrating AI models into customer-facing SaaS dashboards and APIs Success Metrics Transcription accuracy improvement by ≥15% across core languages within 6 months End-to-end voice-to-nudge latency reduced below 5 seconds GenAI assistant adoption across 70%+ of eligible conversations AI-driven call scoring rolled out across 100% of Tier 1 clients within 9 months Model deployment velocity (dev to prod) reduced by ≥40% through tooling and process improvements Culture at Darwix AI At Darwix AI, we operate at the intersection of engineering velocity and product clarity. We move fast, prioritize outcomes over optics, and expect leaders to drive hands-on impact. You will work directly with the founding team and senior leaders across engineering, product, and GTM functions. Expect ownership, direct communication, and a culture that values builders who scale systems, people, and strategy. Compensation and Benefits Competitive fixed compensation Performance-based bonuses and growth-linked incentives ESOP eligibility for leadership candidates Access to GPU/compute credits and model experimentation infrastructure Comprehensive medical insurance and wellness programs Dedicated learning and development budget for technical and leadership upskilling MacBook Pro, premium workstation, and access to industry tooling licenses Career Progression 12-month roadmap: Build and stabilize AI platform across all product lines 18–24-month horizon: Elevate to VP of AI or Chief AI Officer as platform scale increases globally Future leadership role in enabling new verticals (e.g., healthcare, finance, logistics) with domain-specific GenAI solutions How to Apply Send the following to careers@darwix.ai : Updated CV (PDF format) A short statement (200 words max) on: “How would you design a multilingual voice-to-text pipeline optimized for low-resource Indic languages, with real-time nudge delivery?” Links to any relevant GitHub repos, publications, or deployed projects (optional) Subject Line : “Application – Head of AI & ML Platforms – [Your Name]”

Company : Ultrasafe AI Business Type : Small/Medium Type : Product & Model : Stage : : Emerging Technologies Job Description About UltraSafeAI is a US-based technology company at the forefront of developing secure, reliable, and explainable AI systems. We specialize in proprietary AI technologies including advanced LLMs, CNNs, VLLMs, intelligent agents, computer vision systems, and cutting-edge ML algorithms. Our focus is on B2B AI adoption, providing end-to-end integration using our proprietary technology stack to automate entire business processes. We create intelligent solutions that prioritize safety, transparency, and human alignment across various industries including healthcare, finance, legal, and enterprise services. Our mission is to enable seamless AI adoption while maintaining the highest standards of safety and ethical considerations. Position Overview We're seeking experienced Python Engineers with expertise in building modern AI systems, particularly focusing on Retrieval Augmented Generation (RAG) architectures and agentic AI frameworks. The ideal candidate will have strong experience with FastAPI, vector databases, and orchestrating complex AI agents to solve real-world problems. As a Python Engineer at UltraSafeAI, you'll work on designing and implementing scalable, secure AI systems that power our clients' critical business processes. You'll collaborate with a global team of engineers, researchers, and domain experts to create solutions that set new standards for safety and reliability in AI. Key Responsibilities Design and develop robust FastAPI applications that serve as the backbone for our AI systems. Implement sophisticated RAG (Retrieval Augmented Generation) architectures utilizing vector databases, embeddings, and reranking techniques. Build and orchestrate multi-agent AI systems using frameworks like LangGraph, CrewAI, or Agent Development Kit. Develop intelligent knowledge retrieval systems that enhance LLM capabilities with domain-specific information. Create scalable, maintainable, and well-tested code that meets our high-quality standards. Contribute to architecture decisions and technology selection for new projects. Collaborate with cross-functional teams to understand requirements and deliver solutions. Participate in code reviews and knowledge sharing to elevate the entire engineering team. Stay current with the rapidly evolving AI landscape and recommend new approaches. Required Qualifications Strong expertise in FastAPI development with authentication, async processing, and API design. Practical experience building RAG systems with vector databases (Pinecone, FAISS, Chroma, Qdrant, etc.). Experience with embedding models and techniques for effective information retrieval. Hands-on experience with at least one agentic framework (LangGraph, CrewAI, Agent Development Kit, etc.). Solid understanding of LLMs and their integration into production systems. Excellent problem-solving skills and attention to detail. Strong communication skills and ability to work in a distributed team. Self-motivated with the ability to work independently in a remote environment. Highly Desirable Experience with specialized vector database operations and optimizations. Knowledge of reranking techniques to improve retrieval quality. Experience building complex multi-agent systems that coordinate specialized AI agents. Background in specific domains like finance, healthcare, or legal. Contributions to open-source projects. Understanding of AI safety considerations and alignment techniques. Experience with deployment and monitoring of AI systems in production. Why Join UltraSafeAI? 100% Remote Work : Work from anywhere in the world with flexible hours. Cutting-Edge Technology : Build systems using the latest advancements in AI. Meaningful Impact : Create AI solutions that prioritize safety and human wellbeing. Continuous Learning : Regular knowledge sharing sessions and education stipend. Global Team : Collaborate with talented professionals from diverse backgrounds. Work-Life Balance : Flexible PTO policy and respect for personal time. Career Growth : Clear paths for advancement in a rapidly growing company. Modern Tech Stack : Work with the latest tools and technologies in AI development. Remote Work Environment At UltraSafeAI, We've Built a Fully Distributed Team From Day One. We Believe Talent Is Global, And We've Created Processes And Tools To Ensure Remote Work Is Efficient, Collaborative, And Enjoyable. Asynchronous-first communication with minimal required meetings. Collaborative documentation and knowledge management. Regular virtual team-building events and optional in-person retreats. Flexible working hours with core collaboration Process : Initial application review. Technical interviews with the engineering team. Technical assessment. Code review and discussion of your assessment. Final interview with leadership. Offer. Important Note Regarding The Technical Assessment Our technical assessment is designed to evaluate your actual skills and problem-solving abilities. We expect candidates to complete the assessment independently without using AI tools or external help. During the interview process, you will be asked to explain your code and may be required to write similar solutions in real-time. Any discrepancies between your assessment performance and interview performance will be carefully considered in our hiring decision. Join Us In Building Safer AI If you're passionate about creating AI systems that are not only powerful but also safe, transparent, and aligned with human values, we'd love to hear from you. At UltraSafeAI, you'll help shape the future of AI technology while working with a global team of talented, mission-driven professionals. (ref:hirist.tech)

Working with Us Challenging. Meaningful. Life-changing. Those aren't words that are usually associated with a job. But working at Bristol Myers Squibb is anything but usual. Here, uniquely interesting work happens every day, in every department. From optimizing a production line to the latest breakthroughs in cell therapy, this is work that transforms the lives of patients, and the careers of those who do it. You'll get the chance to grow and thrive through opportunities uncommon in scale and scope, alongside high-achieving teams. Take your career farther than you thought possible. Bristol Myers Squibb recognizes the importance of balance and flexibility in our work environment. We offer a wide variety of competitive benefits, services and programs that provide our employees with the resources to pursue their goals, both at work and in their personal lives. Read more careers.bms.com/working-with-us . Summary As a Data Engineer based out of our BMS Hyderabad you are part of the Data Platform team along with supporting the larger Data Engineering community, that delivers data and analytics capabilities for Data Platforms and Data Engineering Community. The ideal candidate will have a strong background in data engineering, DataOps, cloud native services, and will be comfortable working with both structured and unstructured data. Key Responsibilities The Data Engineer will be responsible for designing, building, and maintaining the data products, evolution of the data products, and utilize the most suitable data architecture required for our organization's data needs. Serves as the Subject Matter Expert on Data & Analytics Solutions. Accountable for delivering high quality, data products and analytic ready data solutions. Develop and maintain ETL/ELT pipelines for ingesting data from various sources into our data warehouse. Develop and maintain data models to support our reporting and analysis needs. Optimize data storage and retrieval to ensure efficient performance and scalability. Collaborate with data architects, data analysts and data scientists to understand their data needs and ensure that the data infrastructure supports their requirements. Ensure data quality and integrity through data validation and testing. Implement and maintain security protocols to protect sensitive data. Stay up-to-date with emerging trends and technologies in data engineering and analytics Closely partner with the Enterprise Data and Analytics Platform team, other functional data teams and Data Community lead to shape and adopt data and technology strategy. Accountable for evaluating Data enhancements and initiatives, assessing capacity and prioritization along with onshore and vendor teams. Knowledgeable in evolving trends in Data platforms and Product based implementation Manage and provide guidance for the data engineers supporting projects, enhancements, and break/fix efforts. Has end-to-end ownership mindset in driving initiatives through completion Comfortable working in a fast-paced environment with minimal oversight Mentors and provide career guidance to other team members effectively to unlock full potential. Prior experience working in an Agile/Product based environment. Provides strategic feedback to vendors on service delivery and balances workload with vendor teams. Qualifications & Experience Hands-on experience working on implementing and operating data capabilities and cutting-edge data solutions, preferably in a cloud environment. Breadth of experience in technology capabilities that span the full life cycle of data management including data lakehouses, master/reference data management, data quality and analytics/AI ML. Ability to craft and architect data solutions, automation pipelines to productionize solutions. Hands-on experience developing and delivering data, ETL solutions with some of the technologies like AWS data services (Glue, Redshift, Athena, lakeformation, etc.). Cloudera Data Platform, Tableau labs is a plus. Create and maintain optimal data pipeline architecture, assemble large, complex data sets that meet functional / non-functional business requirements. Identify, design, and implement internal process improvements automating manual processes, optimizing data delivery, re-designing infrastructure for greater scalability, etc. Strong programming skills in languages such as Python, PySpark, R, PyTorch, Pandas, Scala etc. Experience with SQL and database technologies such as MySQL, PostgreSQL, Presto, etc. Experience with cloud-based data technologies such as AWS, Azure, or GCP (Preferably strong in AWS) Strong analytical and problem-solving skills Excellent communication and collaboration skills Functional knowledge or prior experience in Lifesciences Research and Development domain is a plus Experience and expertise in establishing agile and product-oriented teams that work effectively with teams in US and other global BMS site. Initiates challenging opportunities that build strong capabilities for self and team Demonstrates a focus on improving processes, structures, and knowledge within the team. Leads in analyzing current states, deliver strong recommendations in understanding complexity in the environment, and the ability to execute to bring complex solutions to completion. AWS Data Engineering/Analytics certification is a plus. If you come across a role that intrigues you but doesn't perfectly line up with your resume, we encourage you to apply anyway. You could be one step away from work that will transform your life and career. Uniquely Interesting Work, Life-changing Careers With a single vision as inspiring as Transforming patients' lives through science™ , every BMS employee plays an integral role in work that goes far beyond ordinary. Each of us is empowered to apply our individual talents and unique perspectives in a supportive culture, promoting global participation in clinical trials, while our shared values of passion, innovation, urgency, accountability, inclusion and integrity bring out the highest potential of each of our colleagues. On-site Protocol BMS has an occupancy structure that determines where an employee is required to conduct their work. This structure includes site-essential, site-by-design, field-based and remote-by-design jobs. The occupancy type that you are assigned is determined by the nature and responsibilities of your role Site-essential roles require 100% of shifts onsite at your assigned facility. Site-by-design roles may be eligible for a hybrid work model with at least 50% onsite at your assigned facility. For these roles, onsite presence is considered an essential job function and is critical to collaboration, innovation, productivity, and a positive Company culture. For field-based and remote-by-design roles the ability to physically travel to visit customers, patients or business partners and to attend meetings on behalf of BMS as directed is an essential job function. BMS is dedicated to ensuring that people with disabilities can excel through a transparent recruitment process, reasonable workplace accommodations/adjustments and ongoing support in their roles. Applicants can request a reasonable workplace accommodation/adjustment prior to accepting a job offer. If you require reasonable accommodations/adjustments in completing this application, or in any part of the recruitment process, direct your inquiries to adastaffingsupport@bms.com . Visit careers.bms.com/ eeo -accessibility to access our complete Equal Employment Opportunity statement. BMS cares about your well-being and the well-being of our staff, customers, patients, and communities. As a result, the Company strongly recommends that all employees be fully vaccinated for Covid-19 and keep up to date with Covid-19 boosters. BMS will consider for employment qualified applicants with arrest and conviction records, pursuant to applicable laws in your area. If you live in or expect to work from Los Angeles County if hired for this position, please visit this page for important additional information https //careers.bms.com/california-residents/ Any data processed in connection with role applications will be treated in accordance with applicable data privacy policies and regulations.

The AIN QA Technical Specialist plays a critical role in advancing Quality Assurance initiatives across the Quality Operations Network, with a particular focus on Management Review, Inspections and Compliance, and Technical Writing & Data Analytics. This role provides operational support, technical leadership, and cross-functional collaboration to ensure compliance, continuous improvement, and data-driven decision making in support of the Quality Management System (QMS). The position will be responsible for tasks including the key responsibilities documented below and other technical quality-related job functions. This candidate will primarily work during regular working hours (9 AM – 6 PM local time) to enable the business in delivering Amgen’s mission to serve patients and may lead a shift-based team that provides coverage in support of the Amgen network across multiple time zones. The candidate may need to work outside of his/her routine workday to support business needs and will be responsible for determining the same for their staff. The individual will be required to work from our office located in Hyderabad India (Amgen India-AIN). The candidate will also lead the remote support from AIN to Amgen sites globally. Key Responsibilities - Management Review Coordinate and manage all logistics related to Site Management Review, including compiling metrics, maintaining and updating Smartsheet trackers, and preparing content. Perform site-level and cross-site trend analysis (as applicable) using key quality metrics; identify trends and collaborate with site stakeholders to implement corrective and preventive actions (CAPA). Lead preparation of Management Review meetings, ensuring comprehensive data presentation creation, documentation of meeting minutes, and follow-up on action items. Inspections and Compliance Support readiness and response for internal and external inspections, including generation of pre-inspection documents such as deviation lists, change controls, and supporting evidence. Actively contribute during inspections by managing information requests, facilitating document electronic retrieval, and preparing responses in collaboration with subject matter experts. Lead Site Master File updates by coordinating content input from cross-functional stakeholders, drafting revisions, and managing review and approval workflows. Technical Writing and Data Analytics Lead authoring and workflow coordination for periodic quality trend reports and related documentation. Generate deviation summary reports to support product and process monitoring efforts, ensuring accuracy and consistency with cGMP standards. Drive quality risk assessments, providing technical leadership in risk identification, analysis, and mitigation planning in alignment with standards. Preferred Qualifications Demonstrated experience in a GMP-compliant environment with working knowledge of inspection protocols, site audits, and quality risk management principles. Proficiency in technical writing and data visualization tools; experience with Smartsheet, Tableau, or equivalent platforms preferred. Strong analytical skills with the ability to interpret data trends and drive improvements based on quality insights. Familiarity with electronic quality systems (e.g., Veeva, TrackWise, SAP-QM, LIMS) and documentation practices. Excellent verbal and written communication skills, including experience presenting to senior leaders. Proven ability to lead and collaborate within cross-functional teams in a dynamic, fast-paced setting. Core Competencies Leadership in Quality Governance (e.g., Management Review) Inspection Readiness and Compliance Assurance Quality Data Visualization, Interpretation and Analytics Technical Document Drafting and Workflow Ownership Cross-Functional Stakeholder Engagement Continuous Improvement Mindset Basic Qualifications and Experience: Master’s degree with 8-13 years of Pharma and Biotech commercial or clinical manufacturing Quality experience.

The AIN QA Technical Resource Team Senior Manager will play a critical role in advancing Quality Assurance initiatives across the Quality Operations Network, with a particular focus on leading and directing a team of quality professionals responsible for the support of Management Review, Inspections and Compliance, and Technical Writing & Data Analytics. The senior manager will use strategic planning and prioritization to support the collective requirements of the Quality organization alongside the individual needs and timelines of the sites. The individual will be required to work from our office located in Hyderabad India (Amgen India-AIN). The candidate will also lead the remote support from AIN to Amgen sites across multiple time zones globally This candidate will primarily work during regular working hours (9 am – 6 PM local time) to enable the business in delivering Amgen’s mission to serve patients and may lead a shift-based team that provides coverage in support of the Amgen network across multiple time zones. The candidate may need to work outside of his/her routine workday to support business needs and will be responsible for determining the same for their staff. As Senior Manager in the Quality Assurance organization, you’re in a leadership position with responsibilities to supervise and mentor staff. As a leader, you will focus your efforts on the following functions in support of global Quality Assurance operations: Focus Areas This role provides operational support, technical leadership, and cross-functional collaboration to ensure compliance, continuous improvement, and data-driven decision making in support of the Quality Management System (QMS). Oversight of the AIN-based Quality Assurance Technical Resource team Collaboration with the global quality leaders and business process owner(s) to resolve issues encountered by the team Management of request prioritization in alignment with QA network needs Support staff training, career development and performance management of team across all three shifts Responsible for ensuring compliance with safety guidelines, cGMPs and other applicable regulatory requirements Champion process improvements to increase efficiency and productivity Assign workload appropriately and strategically based on required interactions with sites in the Amgen network across multiple time zones The following are some examples of tasks for the position Support of management review (MR) at each Amgen site through collaboration with Amgen leadership and coordination of the AIN technical support team to provide MR (management review) logistical support, metrics/KPI’s, meeting agenda/content, site-level and cross-site trend analysis, and meeting facilitation. Leading the team responsible to provide readiness and response for internal and external inspections, including generation of pre-inspection documents such as deviation lists, change controls, and supporting evidence. Actively contribute during inspections by managing team to provide timely response to information requests, facilitating document electronic retrieval, and preparing responses in collaboration with subject matter experts. Leading a technical writing and data analytics workstream that includes responsibility for periodic quality trend report authorship, Site Master File authoring, product and process monitoring deviation summary reports, and leading quality risk management processes. Preferred Qualifications Strong project management skills and experience supervising professionals in a Quality organization working with cross functional and global stakeholders across multiple time zones Working knowledge of cGMP regulations Excellent written and verbal communication skills, ability to work in a team environment and build relationships with partners Track record of building and maintaining a high performing team Experience with various Quality Systems and applications Strong leadership and negotiation skills with a demonstrated ability to influence others Demonstrated innovative thinking and ability to transform work organizations Demonstrated ability to navigate through ambiguity and provide structured problem solving Demonstrated ability to deliver right the first time on schedule in accordance with established Service Level Agreements Demonstrated skills in staff motivation, coaching/mentoring and professional development Basic Qualifications and Experience: Master’s degree with 12-16 years of Pharma and Biotech commercial or clinical manufacturing Quality experience.

AI Engineer – Voice, NLP, and GenAI Systems Location : Sector 63, Gurgaon – 100% In-Office Working Days : Monday to Friday, with 2nd and 4th Saturdays off Working Hours : 10:30 AM to 8:00 PM Experience : 2–6 years in AI/ML, NLP, or applied machine learning engineering Apply at : careers@darwix.ai Subject Line : Application – AI Engineer – [Your Name] About Darwix AI Darwix AI is India’s fastest-growing GenAI SaaS platform transforming how enterprise sales, field, and support teams engage with customers. Our suite— Transform+ , Sherpa.ai , and Store Intel —powers real-time multilingual voice analytics, AI nudges, coaching systems, and computer vision analytics for major enterprises across India, MENA, and Southeast Asia. We work with some of the largest names such as Aditya Birla Capital, Sobha, GIVA, and Bank Dofar. Our systems process thousands of daily conversations, live call transcripts, and omnichannel data to deliver actionable revenue insights and in-the-moment enablement. Role Overview As an AI Engineer , you will play a key role in designing, developing, and scaling AI and NLP systems that power our core products. You will work at the intersection of voice AI, natural language processing (NLP), large language models (LLMs), and speech-to-text pipelines. You will collaborate with product, backend, and frontend teams to integrate ML models into production workflows, optimize inference pipelines, and improve the accuracy and performance of real-time analytics used by enterprise sales and field teams. Key ResponsibilitiesAI & NLP System Development Design, train, fine-tune, and deploy NLP models for conversation analysis, scoring, sentiment detection, and call summarization. Work on integrating and customizing speech-to-text (STT) pipelines (e.g., WhisperX, Deepgram) for multilingual audio data. Develop and maintain classification, extraction, and sequence-to-sequence models to handle real-world sales and service conversations. LLM & Prompt Engineering Experiment with and integrate large language models (OpenAI, Cohere, open-source LLMs) for live coaching and knowledge retrieval use cases. Optimize prompts and design retrieval-augmented generation (RAG) workflows to support real-time use in product modules. Develop internal tools for model evaluation and prompt performance tracking. Productionization & Integration Build robust model APIs and microservices in collaboration with backend engineers (primarily Python, FastAPI). Optimize inference time and resource utilization for real-time and batch processing needs. Implement monitoring and logging for production ML systems to track drift and failure cases. Data & Evaluation Work on audio-text alignment datasets, conversation logs, and labeled scoring data to improve model performance. Build evaluation pipelines and create automated testing scripts for accuracy and consistency checks. Define and track key performance metrics such as WER (word error rate), intent accuracy, and scoring consistency. Collaboration & Research Work closely with product managers to translate business problems into model design requirements. Explore and propose new approaches leveraging the latest research in voice, NLP, and generative AI. Document research experiments, architecture decisions, and feature impact clearly for internal stakeholders. Required Skills & Qualifications 2–6 years of experience in AI/ML engineering, preferably with real-world NLP or voice AI applications. Strong programming skills in Python , including libraries like PyTorch, TensorFlow, Hugging Face Transformers. Experience with speech processing , audio feature extraction, or STT pipelines. Solid understanding of NLP tasks: tokenization, embedding, NER, summarization, intent detection, sentiment analysis. Familiarity with deploying models as APIs and integrating them with production backend systems. Good understanding of data pipelines, preprocessing techniques, and scalable model architectures. Preferred Qualifications Prior experience with multilingual NLP systems or models tuned for Indian languages. Exposure to RAG pipelines , embeddings search (e.g., FAISS, Pinecone), and vector databases. Experience working with voice analytics, diarization, or conversational scoring frameworks. Understanding of DevOps basics for ML (MLflow, Docker, GitHub Actions for model deployment). Experience in SaaS product environments serving enterprise clients. Success in This Role Means Accurate, robust, and scalable AI models powering production workflows with minimal manual intervention. Inference pipelines optimized for enterprise-scale deployments with high availability. New features and improvements delivered quickly to drive direct business impact. AI-driven insights and automations that enhance user experience and boost revenue outcomes for clients. You Will Excel in This Role If You Love building AI systems that create measurable value in the real world, not just in research labs. Enjoy solving messy, real-world data problems and working on multilingual and noisy data. Are passionate about voice and NLP, and constantly follow advancements in GenAI. Thrive in a fast-paced, high-ownership environment where ideas quickly become live features. How to Apply Email your updated CV to careers@darwix.ai Subject Line: Application – AI Engineer – [Your Name] (Optional): Share links to your GitHub, open-source contributions, or a short note about a model or system you designed and deployed in production. This is an opportunity to build foundational AI systems at one of India’s fastest-scaling GenAI startups and to impact how large enterprises engage millions of customers every day. If you are ready to transform how AI meets revenue teams—Darwix AI wants to hear from you.

HCLTech is looking for a highly talented and self- motivated [ Principal Software Engineer to join it in advancing the technological world through innovation and creativity. Job Title: Principal Software Engineer Role/Responsibilities Gen AI capability development - Design, fine-tune, and optimize LLMs, retrieval-augmented generation (RAG), and reinforcement learning models for IT automation. Experiment with cutting-edge AI techniques, including multi-agent architectures, prompt tuning, and continual learning. 6+ years of experience in a similar role, with a strong focus on developing & deploying machine learning models in production environments. Improve model accuracy, latency, and efficiency, ensuring optimal performance for deployed ML applications. Design and implement CI/CD pipelines for deploying machine learning models to production environments Automate the processes involved in training, testing, deploying, and monitoring models to ensure smooth and continuous operations. Develop tools and frameworks for monitoring model performance and stability in production, ensuring models remain accurate and effective over time. Work closely with data scientists and data engineers to integrate machine learning models with existing data infrastructure Manage cloud-based machine learning environments, ensuring scalability, security, and cost-efficiency. Optimize models for production, focusing on performance, scalability, and resource utilization Create and maintain comprehensive documentation for processes, pipelines, and system architecture. Proficiency in Python and demonstrable expertise in at-least one of machine learning frameworks (e.g., TensorFlow, PyTorch, Scikit-learn). Experience with LLMs and finetuning models Experience with CI/CD tools (e.g., Jenkins, GitLab CI, Gitub Actions) and containerization (e.g., Docker, Kubernetes). Hands-on Knowledge of cloud platforms (e.g., AWS, GCP, Azure, Databricks) and cloud-native tools for MLOps. Experience with monitoring and logging tools (e.g., Prometheus, Grafana, ELK Stack). Experience with infrastructure-as-code tools (e.g., Terraform, Ansible). Familiarity with data engineering workflows and ETL processes. Knowledge of model explainability and fairness considerations in production. Working knowledge of Databricks is a huge plus. How You’ll Grow At HCLTech, we offer continuous opportunities for you to find your spark and grow with us. We want you to be happy and satisfied with your role and to really learn what type of work sparks your brilliance the best. Throughout your time with us, we offer transparent communication with senior-level employees, learning and career development programs at every level, and opportunities to experiment in different roles or even pivot industries. We believe that you should be in control of your career with unlimited opportunities to find the role that fits you best.

Job Title: Senior Python Developer – Backend Engineering Company: Darwix AI Location: Gurgaon (On-site) Type: Full-Time Experience Required: 4–8 Years About Darwix AI Darwix AI is building India’s most advanced GenAI-powered platform for enterprise sales teams. We combine speech recognition, LLMs, vector databases, real-time analytics, and multilingual intelligence to power customer conversations across India, the Middle East, and Southeast Asia. We’re solving complex backend problems across speech-to-text pipelines , agent assist systems , AI-based real-time decisioning , and scalable SaaS delivery . Our engineering team sits at the core of our product and works closely with AI research, product, and client delivery to build the future of revenue enablement. Backed by top-tier VCs, AI advisors, and enterprise clients, this is a chance to build something foundational. Role Overview We are hiring a Senior Python Developer to architect, implement, and optimize high-performance backend systems that power our AI platform. You will take ownership of key backend services—from core REST APIs and data pipelines to complex integrations with AI/ML modules. This role is for builders. You’ll work closely with product, AI, and infra teams, write production-grade Python code, lead critical decisions on architecture, and help shape engineering best practices. Key Responsibilities 1. Backend API Development Design and implement scalable, secure RESTful APIs using FastAPI , Flask , or Django REST Framework Architect modular services and microservices to support AI, transcription, real-time analytics, and reporting Optimize API performance with proper indexing, pagination, caching, and load management strategies Integrate with frontend systems, mobile clients, and third-party systems through clean, well-documented endpoints 2. AI Integrations & Inference Orchestration Work closely with AI engineers to integrate GenAI/LLM APIs (OpenAI, Llama, Gemini), transcription models (Whisper, Deepgram), and retrieval-augmented generation (RAG) workflows Build services to manage prompt templates, chaining logic, and LangChain flows Deploy and manage vector database integrations (e.g., FAISS , Pinecone , Weaviate ) for real-time search and recommendation pipelines 3. Database Design & Optimization Model and maintain relational databases using MySQL or PostgreSQL ; experience with MongoDB is a plus Optimize SQL queries, schema design, and indexes to support low-latency data access Set up background jobs for session archiving, transcript cleanup, and audio-data binding 4. System Architecture & Deployment Own backend deployments using GitHub Actions , Docker , and AWS EC2 Ensure high availability of services through containerization, horizontal scaling, and health monitoring Manage staging and production environments, including DB backups, server health checks, and rollback systems 5. Security, Auth & Access Control Implement robust authentication (JWT, OAuth), rate limiting , and input validation Build role-based access controls (RBAC) and audit logging into backend workflows Maintain compliance-ready architecture for enterprise clients (data encryption, PII masking) 6. Code Quality, Documentation & Collaboration Write clean, modular, extensible Python code with meaningful comments and documentation Build test coverage (unit, integration) using PyTest , unittest , or Postman/Newman Participate in pull requests, code reviews, sprint planning, and retrospectives with the engineering team Required Skills & QualificationsTechnical Expertise 3–8 years of experience in backend development with Python, PHP. Strong experience with FastAPI , Flask , or Django (at least one in production-scale systems) Deep understanding of RESTful APIs , microservice architecture, and asynchronous Python patterns Strong hands-on with MySQL (joins, views, stored procedures); bonus if familiar with MongoDB , Redis , or Elasticsearch Experience with containerized deployment using Docker and cloud platforms like AWS or GCP Familiarity with Git , GitHub , CI/CD pipelines , and Linux-based server environments Plus Points Experience working on audio processing , speech-to-text (STT) pipelines, or RAG architectures Hands-on with vector databases or LangChain , LangGraph Exposure to real-time systems, WebSockets, and stream processing Basic understanding of frontend integration workflows (e.g., with HTML/CSS/JS interfaces)

Job description 🚀 Job Title: AI Engineer Company : Darwix AI Location : Gurgaon (On-site) Type : Full-Time Experience : 2-6 Years Level : Senior Level 🌐 About Darwix AI Darwix AI is one of India’s fastest-growing GenAI startups, revolutionizing the future of enterprise sales and customer engagement with real-time conversational intelligence. We are building a GenAI-powered agent-assist and pitch intelligence suite that captures, analyzes, and enhances every customer interaction—across voice, video, and chat—in real time. We serve leading enterprise clients across India, the UAE, and Southeast Asia and are backed by global VCs, top operators from Google, Salesforce, and McKinsey, and CXOs from the industry. This is your opportunity to join a high-caliber founding tech team solving frontier problems in real-time voice AI, multilingual transcription, retrieval-augmented generation (RAG), and fine-tuned LLMs at scale. 🧠 Role Overview As the AI Engineer , you will drive the development, deployment, and optimization of AI systems that power Darwix AI's real-time conversation intelligence platform. This includes voice-to-text transcription, speaker diarization, GenAI summarization, prompt engineering, knowledge retrieval, and real-time nudge delivery. You will lead a team of AI engineers and work closely with product managers, software architects, and data teams to ensure technical excellence, scalable architecture, and rapid iteration cycles. This is a high-ownership, hands-on leadership role where you will code, architect, and lead simultaneously. 🔧 Key Responsibilities 1. AI Architecture & Model Development Architect end-to-end AI pipelines for transcription, real-time inference, LLM integration, and vector-based retrieval. Build, fine-tune, and deploy STT models (Whisper, Wav2Vec2.0) and diarization systems for speaker separation. Implement GenAI pipelines using OpenAI, Gemini, LLaMA, Mistral, and other LLM APIs or open-source models. 2. Real-Time Voice AI System Development Design low-latency pipelines for capturing and processing audio in real-time across multi-lingual environments. Work on WebSocket-based bi-directional audio streaming, chunked inference, and result caching. Develop asynchronous, event-driven architectures for voice processing and decision-making. 3. RAG & Knowledge Graph Pipelines Create retrieval-augmented generation (RAG) systems that pull from structured and unstructured knowledge bases. Build vector DB architectures (e.g., FAISS, Pinecone, Weaviate) and connect to LangChain/LlamaIndex workflows. Own chunking, indexing, and embedding strategies (OpenAI, Cohere, Hugging Face embeddings). 4. Fine-Tuning & Prompt Engineering Fine-tune LLMs and foundational models using RLHF, SFT, PEFT (e.g., LoRA) as needed. Optimize prompts for summarization, categorization, tone analysis, objection handling, etc. Perform few-shot and zero-shot evaluations for quality benchmarking. 5. Pipeline Optimization & MLOps Ensure high availability and robustness of AI pipelines using CI/CD tools, Docker, Kubernetes, and GitHub Actions. Work with data engineering to streamline data ingestion, labeling, augmentation, and evaluation. Build internal tools to benchmark latency, accuracy, and relevance for production-grade AI features. 6. Team Leadership & Cross-Functional Collaboration Lead, mentor, and grow a high-performing AI engineering team. Collaborate with backend, frontend, and product teams to build scalable production systems. Participate in architectural and design decisions across AI, backend, and data workflows. 🛠️ Key Technologies & Tools Languages & Frameworks : Python, FastAPI, Flask, LangChain, PyTorch, TensorFlow, HuggingFace Transformers Voice & Audio : Whisper, Wav2Vec2.0, DeepSpeech, pyannote.audio, AssemblyAI, Kaldi, Mozilla TTS Vector DBs & RAG : FAISS, Pinecone, Weaviate, ChromaDB, LlamaIndex, LangGraph LLMs & GenAI APIs : OpenAI GPT-4/3.5, Gemini, Claude, Mistral, Meta LLaMA 2/3 DevOps & Deployment : Docker, GitHub Actions, CI/CD, Redis, Kafka, Kubernetes, AWS (EC2, Lambda, S3) Databases : MongoDB, Postgres, MySQL, Pinecone, TimescaleDB Monitoring & Logging : Prometheus, Grafana, Sentry, Elastic Stack (ELK) 🎯 Requirements & Qualifications 👨‍💻 Experience 2-6 years of experience in building and deploying AI/ML systems, with at least 2+ years in NLP or voice technologies. Proven track record of production deployment of ASR, STT, NLP, or GenAI models. Hands-on experience building systems involving vector databases, real-time pipelines, or LLM integrations. 📚 Educational Background Bachelor's or Master's in Computer Science, Artificial Intelligence, Machine Learning, or a related field. Tier 1 institute preferred (IITs, BITS, IIITs, NITs, or global top 100 universities). ⚙️ Technical Skills Strong coding experience in Python and familiarity with FastAPI/Django. Understanding of distributed architectures, memory management, and latency optimization. Familiarity with transformer-based model architectures, training techniques, and data pipeline design. 💡 Bonus Experience Worked on multilingual speech recognition and translation. Experience deploying AI models on edge devices or browsers. Built or contributed to open-source ML/NLP projects. Published papers or patents in voice, NLP, or deep learning domains. 🚀 What Success Looks Like in 6 Months Lead the deployment of a real-time STT + diarization system for at least 1 enterprise client. Deliver high-accuracy nudge generation pipeline using RAG and summarization models. Build an in-house knowledge indexing + vector DB framework integrated into the product. Mentor 2–3 AI engineers and own execution across multiple modules. Achieve <1 sec latency on real-time voice-to-nudge pipeline from capture to recommendation. 💼 What We Offer Compensation : Competitive fixed salary + equity + performance-based bonuses Impact : Ownership of key AI modules powering thousands of live enterprise conversations Learning : Access to high-compute GPUs, API credits, research tools, and conference sponsorships Culture : High-trust, outcome-first environment that celebrates execution and learning Mentorship : Work directly with founders, ex-Microsoft, IIT-IIM-BITS alums, and top AI engineers Scale : Opportunity to scale an AI product from 10 clients to 100+ globally within 12 months ⚠️ This Role is NOT for Everyone 🚫 If you're looking for a slow, abstract research role—this is NOT for you. 🚫 If you're used to months of ideation before shipping—you won't enjoy our speed. 🚫 If you're not comfortable being hands-on and diving into scrappy builds—you may struggle. ✅ But if you’re a builder , architect , and visionary —who loves solving hard technical problems and delivering real-time AI at scale, we want to talk to you. 📩 How to Apply Send your CV, GitHub/portfolio, and a brief note on “Why AI at Darwix?” to: 📧 careers@cur8.in Subject Line: Application – AI Engineer – [Your Name] Include links to: Any relevant open-source contributions LLM/STT models you've fine-tuned or deployed RAG pipelines you've worked on 🔍 Final Thought This is not just a job. This is your opportunity to build the world’s most scalable AI sales intelligence platform —from India, for the world.

Job description 🚀 Job Title: ML Engineer Company : Darwix AI Location : Gurgaon (On-site) Type : Full-Time Experience : 2-6 Years Level : Senior Level 🌐 About Darwix AI Darwix AI is one of India’s fastest-growing GenAI startups, revolutionizing the future of enterprise sales and customer engagement with real-time conversational intelligence. We are building a GenAI-powered agent-assist and pitch intelligence suite that captures, analyzes, and enhances every customer interaction—across voice, video, and chat—in real time. We serve leading enterprise clients across India, the UAE, and Southeast Asia and are backed by global VCs, top operators from Google, Salesforce, and McKinsey, and CXOs from the industry. This is your opportunity to join a high-caliber founding tech team solving frontier problems in real-time voice AI, multilingual transcription, retrieval-augmented generation (RAG), and fine-tuned LLMs at scale. 🧠 Role Overview As the ML Engineer , you will drive the development, deployment, and optimization of AI systems that power Darwix AI's real-time conversation intelligence platform. This includes voice-to-text transcription, speaker diarization, GenAI summarization, prompt engineering, knowledge retrieval, and real-time nudge delivery. You will lead a team of AI engineers and work closely with product managers, software architects, and data teams to ensure technical excellence, scalable architecture, and rapid iteration cycles. This is a high-ownership, hands-on leadership role where you will code, architect, and lead simultaneously. 🔧 Key Responsibilities 1. AI Architecture & Model Development Architect end-to-end AI pipelines for transcription, real-time inference, LLM integration, and vector-based retrieval. Build, fine-tune, and deploy STT models (Whisper, Wav2Vec2.0) and diarization systems for speaker separation. Implement GenAI pipelines using OpenAI, Gemini, LLaMA, Mistral, and other LLM APIs or open-source models. 2. Real-Time Voice AI System Development Design low-latency pipelines for capturing and processing audio in real-time across multi-lingual environments. Work on WebSocket-based bi-directional audio streaming, chunked inference, and result caching. Develop asynchronous, event-driven architectures for voice processing and decision-making. 3. RAG & Knowledge Graph Pipelines Create retrieval-augmented generation (RAG) systems that pull from structured and unstructured knowledge bases. Build vector DB architectures (e.g., FAISS, Pinecone, Weaviate) and connect to LangChain/LlamaIndex workflows. Own chunking, indexing, and embedding strategies (OpenAI, Cohere, Hugging Face embeddings). 4. Fine-Tuning & Prompt Engineering Fine-tune LLMs and foundational models using RLHF, SFT, PEFT (e.g., LoRA) as needed. Optimize prompts for summarization, categorization, tone analysis, objection handling, etc. Perform few-shot and zero-shot evaluations for quality benchmarking. 5. Pipeline Optimization & MLOps Ensure high availability and robustness of AI pipelines using CI/CD tools, Docker, Kubernetes, and GitHub Actions. Work with data engineering to streamline data ingestion, labeling, augmentation, and evaluation. Build internal tools to benchmark latency, accuracy, and relevance for production-grade AI features. 6. Team Leadership & Cross-Functional Collaboration Lead, mentor, and grow a high-performing AI engineering team. Collaborate with backend, frontend, and product teams to build scalable production systems. Participate in architectural and design decisions across AI, backend, and data workflows. 🛠️ Key Technologies & Tools Languages & Frameworks : Python, FastAPI, Flask, LangChain, PyTorch, TensorFlow, HuggingFace Transformers Voice & Audio : Whisper, Wav2Vec2.0, DeepSpeech, pyannote.audio, AssemblyAI, Kaldi, Mozilla TTS Vector DBs & RAG : FAISS, Pinecone, Weaviate, ChromaDB, LlamaIndex, LangGraph LLMs & GenAI APIs : OpenAI GPT-4/3.5, Gemini, Claude, Mistral, Meta LLaMA 2/3 DevOps & Deployment : Docker, GitHub Actions, CI/CD, Redis, Kafka, Kubernetes, AWS (EC2, Lambda, S3) Databases : MongoDB, Postgres, MySQL, Pinecone, TimescaleDB Monitoring & Logging : Prometheus, Grafana, Sentry, Elastic Stack (ELK) 🎯 Requirements & Qualifications 👨‍💻 Experience 2-6 years of experience in building and deploying AI/ML systems, with at least 2+ years in NLP or voice technologies. Proven track record of production deployment of ASR, STT, NLP, or GenAI models. Hands-on experience building systems involving vector databases, real-time pipelines, or LLM integrations. 📚 Educational Background Bachelor's or Master's in Computer Science, Artificial Intelligence, Machine Learning, or a related field. Tier 1 institute preferred (IITs, BITS, IIITs, NITs, or global top 100 universities). ⚙️ Technical Skills Strong coding experience in Python and familiarity with FastAPI/Django. Understanding of distributed architectures, memory management, and latency optimization. Familiarity with transformer-based model architectures, training techniques, and data pipeline design. 💡 Bonus Experience Worked on multilingual speech recognition and translation. Experience deploying AI models on edge devices or browsers. Built or contributed to open-source ML/NLP projects. Published papers or patents in voice, NLP, or deep learning domains. 🚀 What Success Looks Like in 6 Months Lead the deployment of a real-time STT + diarization system for at least 1 enterprise client. Deliver high-accuracy nudge generation pipeline using RAG and summarization models. Build an in-house knowledge indexing + vector DB framework integrated into the product. Mentor 2–3 AI engineers and own execution across multiple modules. Achieve <1 sec latency on real-time voice-to-nudge pipeline from capture to recommendation. 💼 What We Offer Compensation : Competitive fixed salary + equity + performance-based bonuses Impact : Ownership of key AI modules powering thousands of live enterprise conversations Learning : Access to high-compute GPUs, API credits, research tools, and conference sponsorships Culture : High-trust, outcome-first environment that celebrates execution and learning Mentorship : Work directly with founders, ex-Microsoft, IIT-IIM-BITS alums, and top AI engineers Scale : Opportunity to scale an AI product from 10 clients to 100+ globally within 12 months ⚠️ This Role is NOT for Everyone 🚫 If you're looking for a slow, abstract research role—this is NOT for you. 🚫 If you're used to months of ideation before shipping—you won't enjoy our speed. 🚫 If you're not comfortable being hands-on and diving into scrappy builds—you may struggle. ✅ But if you’re a builder , architect , and visionary —who loves solving hard technical problems and delivering real-time AI at scale, we want to talk to you. 📩 How to Apply Send your CV, GitHub/portfolio, and a brief note on “Why AI at Darwix?” to: 📧 careers@cur8.in / vishnu.sethi@cur8.in Subject Line: Application – ML Engineer – [Your Name] Include links to: Any relevant open-source contributions LLM/STT models you've fine-tuned or deployed RAG pipelines you've worked on 🔍 Final Thought This is not just a job. This is your opportunity to build the world’s most scalable AI sales intelligence platform —from India, for the world.

Job Description: Director of Engineering Company: Darwix AI Location: Gurgaon (On-site) Type: Full-Time Experience: 8–12 Years About Darwix AI Darwix AI is a next-generation Gen-AI-powered sales enablement platform that empowers enterprise sales teams with intelligent nudges, real-time insights, and AI-driven conversation analytics. By combining AI, automation, and contextual intelligence, we are redefining how sales teams engage, close, and scale. Backed by leading VCs and industry leaders, Darwix AI is one of the fastest-growing AI startups in India, with an expanding presence across MENA, India, and the US. Role Overview We are seeking a highly experienced and technically proficient Director of Engineering to lead and scale our engineering team. In this role, you will be responsible for managing backend development, DevOps, and infrastructure initiatives. The ideal candidate will be a hands-on technical leader with a strong architectural foundation and proven experience scaling engineering teams and systems in high-growth environments. You will work closely with the Vice President of Engineering and Founders to drive engineering excellence, ensure timely delivery, and lead technical decision-making aligned with business goals. Key Responsibilities Engineering Leadership Lead engineering execution across backend services (Python, PHP), infrastructure, and DevOps. Define technical strategy and ensure alignment with product and organizational goals. Own the delivery roadmap and ensure timely and high-quality outputs. System Architecture and Scalability Oversee backend architecture to ensure reliability, scalability, and performance. Guide the implementation of microservices, RESTful APIs, and scalable cloud-based infrastructure. Design and review systems with considerations for high-volume data ingestion and low-latency processing. Team Management and Development Build, lead, and mentor a high-performing engineering team. Implement best practices for code quality, testing, deployment, and team collaboration. Foster a strong engineering culture focused on learning, execution, and accountability. Cross-Functional Collaboration Collaborate with product, AI/ML, sales, and design teams to align engineering deliverables with business priorities. Translate product requirements into structured engineering plans and milestones. Cloud Infrastructure and DevOps Work closely with the DevOps function to manage AWS cloud infrastructure, CI/CD pipelines, and security protocols. Ensure system uptime, data integrity, and disaster recovery preparedness. AI Infrastructure Support Support integration with LLMs and AI/ML models. Lead initiatives involving vector databases (e.g., FAISS, Pinecone, Weaviate) and retrieval-augmented generation pipelines. Qualifications Education Bachelor's or Master’s degree in Computer Science, Engineering, or a related technical discipline. Candidates from premier institutions (IITs, BITS, NITs) will be preferred. Experience 8–12 years of progressive engineering experience with at least 3 years in a leadership role. Proven experience in building scalable backend systems and managing high-performing engineering teams. Strong exposure to Python and PHP/NodeJS in production-grade systems. Experience in designing and managing infrastructure on AWS or equivalent cloud platforms. Familiarity with containerization (Docker, Kubernetes) and CI/CD systems. Desirable Skills Experience working with vector databases, embeddings, and AI/ML deployment in production. Deep understanding of microservices architecture, event-driven systems, and RESTful API design. Strong communication and stakeholder management skills. What We Offer Leadership role in a fast-scaling, venture-backed AI technology firm. Opportunity to work on large-scale AI applications in real-world enterprise environments. Competitive compensation including fixed salary, ESOPs, and performance-based bonuses. A high-performance culture that encourages ownership, innovation, and continuous learning. Direct collaboration with senior leadership on strategic initiatives. Application Note: This role demands both technical expertise and strategic foresight. We are looking for leaders who are comfortable building systems hands-on, mentoring teams, and ensuring consistent execution in a high-growth, high-ownership environment.

Job Description Must Have Skills: Extensive knowledge of large language models, natural language processing techniques and prompt engineering. Experience in testing and validation processes to ensure the models' accuracy and efficiency in real-world scenarios. Experience in design, build, and deployment of innovative applications utilizing Gen AI technologies such as RAG (Retrieval-Augmented Generation) based chatbots or AI Agents. Proficiency in programming using Python or Java. Familiarity with Oracle Cloud Infrastructure or similar cloud platforms. Effective communication and presentation skills. Analyzes problems, identifies solutions, and makes decisions. Demonstrates a willingness to learn, adapt, and grow professionally. Good to Have Skills: Experience in LLM architectures, model evaluation, and fine-tuning techniques. Hands-on experience with emerging LLM frameworks and plugins, such as LangChain, LlamaIndex, VectorStores and Retrievers, TensorFlow, PyTorch, LLM Cache, LLMOps (MLFlow), LMQL, Guidance, etc. Proficiency in databases (e.g., Oracle, MySQL), developing and executing AI over any of the cloud data platforms, associated data stores, Graph Stores, Vector Stores and pipelines. Understanding of the security and compliance requirements for ML/GenAI implementations. Career Level - IC2/IC3 Responsibilities As a member of Oracle Cloud LIFT, you’ll help guide our customers from concept to successful cloud deployment. You’ll: Shape architecture and solution design with best practices and experience. Own the delivery of agreed workload implementations. Validate and test deployed solutions. Conduct security assurance reviews. You’ll work in a fast-paced, international environment, engaging with customers across industries and regions. You’ll collaborate with peers, sales, architects, and consulting teams to make cloud transformation real. https://www.oracle.com/in/cloud/cloud-lift/ Qualifications Career Level - IC2 About Us As a world leader in cloud solutions, Oracle uses tomorrow’s technology to tackle today’s challenges. We’ve partnered with industry-leaders in almost every sector—and continue to thrive after 40+ years of change by operating with integrity. We know that true innovation starts when everyone is empowered to contribute. That’s why we’re committed to growing an inclusive workforce that promotes opportunities for all. Oracle careers open the door to global opportunities where work-life balance flourishes. We offer competitive benefits based on parity and consistency and support our people with flexible medical, life insurance, and retirement options. We also encourage employees to give back to their communities through our volunteer programs. We’re committed to including people with disabilities at all stages of the employment process. If you require accessibility assistance or accommodation for a disability at any point, let us know by emailing accommodation-request_mb@oracle.com or by calling +1 888 404 2494 in the United States. Oracle is an Equal Employment Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, sexual orientation, gender identity, disability and protected veterans’ status, or any other characteristic protected by law. Oracle will consider for employment qualified applicants with arrest and conviction records pursuant to applicable law.

Job Description Must Have Skills: Extensive knowledge of large language models, natural language processing techniques and prompt engineering. Experience in testing and validation processes to ensure the models' accuracy and efficiency in real-world scenarios. Experience in design, build, and deployment of innovative applications utilizing Gen AI technologies such as RAG (Retrieval-Augmented Generation) based chatbots or AI Agents. Proficiency in programming using Python or Java. Familiarity with Oracle Cloud Infrastructure or similar cloud platforms. Effective communication and presentation skills. Analyzes problems, identifies solutions, and makes decisions. Demonstrates a willingness to learn, adapt, and grow professionally. Good to Have Skills: Experience in LLM architectures, model evaluation, and fine-tuning techniques. Hands-on experience with emerging LLM frameworks and plugins, such as LangChain, LlamaIndex, VectorStores and Retrievers, TensorFlow, PyTorch, LLM Cache, LLMOps (MLFlow), LMQL, Guidance, etc. Proficiency in databases (e.g., Oracle, MySQL), developing and executing AI over any of the cloud data platforms, associated data stores, Graph Stores, Vector Stores and pipelines. Understanding of the security and compliance requirements for ML/GenAI implementations. Career Level - IC2/IC3 Responsibilities As a member of Oracle Cloud LIFT, you’ll help guide our customers from concept to successful cloud deployment. You’ll: Shape architecture and solution design with best practices and experience. Own the delivery of agreed workload implementations. Validate and test deployed solutions. Conduct security assurance reviews. You’ll work in a fast-paced, international environment, engaging with customers across industries and regions. You’ll collaborate with peers, sales, architects, and consulting teams to make cloud transformation real. https://www.oracle.com/in/cloud/cloud-lift/ Qualifications Career Level - IC2 About Us As a world leader in cloud solutions, Oracle uses tomorrow’s technology to tackle today’s challenges. We’ve partnered with industry-leaders in almost every sector—and continue to thrive after 40+ years of change by operating with integrity. We know that true innovation starts when everyone is empowered to contribute. That’s why we’re committed to growing an inclusive workforce that promotes opportunities for all. Oracle careers open the door to global opportunities where work-life balance flourishes. We offer competitive benefits based on parity and consistency and support our people with flexible medical, life insurance, and retirement options. We also encourage employees to give back to their communities through our volunteer programs. We’re committed to including people with disabilities at all stages of the employment process. If you require accessibility assistance or accommodation for a disability at any point, let us know by emailing accommodation-request_mb@oracle.com or by calling +1 888 404 2494 in the United States. Oracle is an Equal Employment Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, sexual orientation, gender identity, disability and protected veterans’ status, or any other characteristic protected by law. Oracle will consider for employment qualified applicants with arrest and conviction records pursuant to applicable law.

🚀 Job Title: Lead AI Engineer Company : Darwix AI Location : Gurgaon (On-site) Type : Full-Time Experience : 2-6 Years Level : Senior Level 🌐 About Darwix AI Darwix AI is one of India’s fastest-growing GenAI startups, revolutionizing the future of enterprise sales and customer engagement with real-time conversational intelligence. We are building a GenAI-powered agent-assist and pitch intelligence suite that captures, analyzes, and enhances every customer interaction—across voice, video, and chat—in real time. We serve leading enterprise clients across India, the UAE, and Southeast Asia and are backed by global VCs, top operators from Google, Salesforce, and McKinsey, and CXOs from the industry. This is your opportunity to join a high-caliber founding tech team solving frontier problems in real-time voice AI, multilingual transcription, retrieval-augmented generation (RAG), and fine-tuned LLMs at scale. 🧠 Role Overview As the Lead AI Engineer , you will drive the development, deployment, and optimization of AI systems that power Darwix AI's real-time conversation intelligence platform. This includes voice-to-text transcription, speaker diarization, GenAI summarization, prompt engineering, knowledge retrieval, and real-time nudge delivery. You will lead a team of AI engineers and work closely with product managers, software architects, and data teams to ensure technical excellence, scalable architecture, and rapid iteration cycles. This is a high-ownership, hands-on leadership role where you will code, architect, and lead simultaneously. 🔧 Key Responsibilities 1. AI Architecture & Model Development Architect end-to-end AI pipelines for transcription, real-time inference, LLM integration, and vector-based retrieval. Build, fine-tune, and deploy STT models (Whisper, Wav2Vec2.0) and diarization systems for speaker separation. Implement GenAI pipelines using OpenAI, Gemini, LLaMA, Mistral, and other LLM APIs or open-source models. 2. Real-Time Voice AI System Development Design low-latency pipelines for capturing and processing audio in real-time across multi-lingual environments. Work on WebSocket-based bi-directional audio streaming, chunked inference, and result caching. Develop asynchronous, event-driven architectures for voice processing and decision-making. 3. RAG & Knowledge Graph Pipelines Create retrieval-augmented generation (RAG) systems that pull from structured and unstructured knowledge bases. Build vector DB architectures (e.g., FAISS, Pinecone, Weaviate) and connect to LangChain/LlamaIndex workflows. Own chunking, indexing, and embedding strategies (OpenAI, Cohere, Hugging Face embeddings). 4. Fine-Tuning & Prompt Engineering Fine-tune LLMs and foundational models using RLHF, SFT, PEFT (e.g., LoRA) as needed. Optimize prompts for summarization, categorization, tone analysis, objection handling, etc. Perform few-shot and zero-shot evaluations for quality benchmarking. 5. Pipeline Optimization & MLOps Ensure high availability and robustness of AI pipelines using CI/CD tools, Docker, Kubernetes, and GitHub Actions. Work with data engineering to streamline data ingestion, labeling, augmentation, and evaluation. Build internal tools to benchmark latency, accuracy, and relevance for production-grade AI features. 6. Team Leadership & Cross-Functional Collaboration Lead, mentor, and grow a high-performing AI engineering team. Collaborate with backend, frontend, and product teams to build scalable production systems. Participate in architectural and design decisions across AI, backend, and data workflows. 🛠️ Key Technologies & Tools Languages & Frameworks : Python, FastAPI, Flask, LangChain, PyTorch, TensorFlow, HuggingFace Transformers Voice & Audio : Whisper, Wav2Vec2.0, DeepSpeech, pyannote.audio, AssemblyAI, Kaldi, Mozilla TTS Vector DBs & RAG : FAISS, Pinecone, Weaviate, ChromaDB, LlamaIndex, LangGraph LLMs & GenAI APIs : OpenAI GPT-4/3.5, Gemini, Claude, Mistral, Meta LLaMA 2/3 DevOps & Deployment : Docker, GitHub Actions, CI/CD, Redis, Kafka, Kubernetes, AWS (EC2, Lambda, S3) Databases : MongoDB, Postgres, MySQL, Pinecone, TimescaleDB Monitoring & Logging : Prometheus, Grafana, Sentry, Elastic Stack (ELK) 🎯 Requirements & Qualifications 👨‍💻 Experience 2-6 years of experience in building and deploying AI/ML systems, with at least 2+ years in NLP or voice technologies. Proven track record of production deployment of ASR, STT, NLP, or GenAI models. Hands-on experience building systems involving vector databases, real-time pipelines, or LLM integrations. 📚 Educational Background Bachelor's or Master's in Computer Science, Artificial Intelligence, Machine Learning, or a related field. Tier 1 institute preferred (IITs, BITS, IIITs, NITs, or global top 100 universities). ⚙️ Technical Skills Strong coding experience in Python and familiarity with FastAPI/Django. Understanding of distributed architectures, memory management, and latency optimization. Familiarity with transformer-based model architectures, training techniques, and data pipeline design. 💡 Bonus Experience Worked on multilingual speech recognition and translation. Experience deploying AI models on edge devices or browsers. Built or contributed to open-source ML/NLP projects. Published papers or patents in voice, NLP, or deep learning domains. 🚀 What Success Looks Like in 6 Months Lead the deployment of a real-time STT + diarization system for at least 1 enterprise client. Deliver high-accuracy nudge generation pipeline using RAG and summarization models. Build an in-house knowledge indexing + vector DB framework integrated into the product. Mentor 2–3 AI engineers and own execution across multiple modules. Achieve <1 sec latency on real-time voice-to-nudge pipeline from capture to recommendation. 💼 What We Offer Compensation : Competitive fixed salary + equity + performance-based bonuses Impact : Ownership of key AI modules powering thousands of live enterprise conversations Learning : Access to high-compute GPUs, API credits, research tools, and conference sponsorships Culture : High-trust, outcome-first environment that celebrates execution and learning Mentorship : Work directly with founders, ex-Microsoft, IIT-IIM-BITS alums, and top AI engineers Scale : Opportunity to scale an AI product from 10 clients to 100+ globally within 12 months ⚠️ This Role is NOT for Everyone 🚫 If you're looking for a slow, abstract research role—this is NOT for you. 🚫 If you're used to months of ideation before shipping—you won't enjoy our speed. 🚫 If you're not comfortable being hands-on and diving into scrappy builds—you may struggle. ✅ But if you’re a builder , architect , and visionary —who loves solving hard technical problems and delivering real-time AI at scale, we want to talk to you. 📩 How to Apply Send your CV, GitHub/portfolio, and a brief note on “Why AI at Darwix?” to: 📧 careers@cur8.in Subject Line: Application – Lead AI Engineer – [Your Name] Include links to: Any relevant open-source contributions LLM/STT models you've fine-tuned or deployed RAG pipelines you've worked on 🔍 Final Thought This is not just a job. This is your opportunity to build the world’s most scalable AI sales intelligence platform —from India, for the world.

Job Title: Lead Backend Developer (Python & Microservices) Company: Darwix AI Location: Gurgaon (On-site) Type: Full-Time Experience Required: 6–10 years About Darwix AI Darwix AI is at the forefront of building the future of revenue enablement through a GenAI-powered conversational intelligence and real-time agent assist platform. Our mission is to empower global sales teams to close better, faster, and smarter by harnessing the transformative power of Generative AI, real-time speech recognition, multilingual insights, and next-gen sales analytics. Backed by top venture capitalists and industry leaders, Darwix AI is scaling rapidly across India, MENA, and US markets. With a leadership team from IIT, IIM, and BITS, we are building enterprise-grade SaaS solutions that are poised to redefine how organizations engage with customers. If you are looking for a role where your work directly powers mission-critical AI applications used globally, this is your moment. Role Overview We are seeking a Lead Backend Developer (Python & Microservices) to drive the architecture, scalability, and performance of our GenAI platform's core backend services. You will own the responsibility of designing, building, and leading backend systems that are real-time, distributed, and capable of supporting AI-powered applications at scale. You will mentor engineers, set technical direction, collaborate across AI, Product, and Frontend teams, and ensure that the backend infrastructure is robust, secure, and future-proof. This is a high-ownership, high-impact role for individuals who are passionate about building world-class systems that are production-ready, scalable, and designed for rapid innovation. Key Responsibilities🔹 Backend Architecture and Development Architect and lead the development of highly scalable, modular, and event-driven backend systems using Python. Build and maintain RESTful APIs and microservices that power real-time, multilingual conversational intelligence platforms. Design systems with a strong focus on scalability, fault tolerance, high availability, and security. Implement API gateways, service registries, authentication/authorization layers, and caching mechanisms. 🔹 Microservices Strategy Champion microservices best practices: service decomposition, asynchronous communication, event-driven workflows. Manage service orchestration, containerization, and scaling using Docker and Kubernetes (preferred). Implement robust service monitoring, logging, and alerting frameworks for proactive system health management. 🔹 Real-time Data Processing Build real-time data ingestion and processing pipelines using tools like Kafka, Redis streams, WebSockets. Integrate real-time speech-to-text (STT) engines and AI/NLP pipelines into backend flows. Optimize performance to achieve low-latency processing suitable for real-time agent assist experiences. 🔹 Database and Storage Management Design and optimize relational (PostgreSQL/MySQL) and non-relational (MongoDB, Redis) database systems. Implement data sharding, replication, and backup strategies for resilience and scalability. Integrate vector databases (FAISS, Pinecone, Chroma) to support AI retrieval and embedding-based search. 🔹 DevOps and Infrastructure Collaborate with DevOps teams to deploy scalable and reliable services on AWS (EC2, S3, Lambda, EKS). Implement CI/CD pipelines, containerization strategies, and blue-green deployment models. Ensure security compliance across all backend services (API security, encryption, RBAC). 🔹 Technical Leadership Mentor junior and mid-level backend engineers. Define and enforce coding standards, architectural patterns, and best practices. Conduct design reviews, code reviews, and ensure high engineering quality across the backend team. 🔹 Collaboration Work closely with AI scientists, Product Managers, Frontend Engineers, and Customer Success teams to deliver delightful product experiences. Translate business needs into technical requirements and backend system designs. Drive sprint planning, estimation, and delivery for backend engineering sprints. Core RequirementsTechnical Skills 6–10 years of hands-on backend engineering experience. Expert-level proficiency in Python . Strong experience building scalable REST APIs and microservices. Deep understanding of FastAPI (preferred) or Flask/Django frameworks. In-depth knowledge of relational (PostgreSQL, MySQL) and NoSQL (MongoDB, Redis) databases. Experience with event-driven architectures: Kafka, RabbitMQ, Redis streams. Proficiency in containerization and orchestration: Docker, Kubernetes. Familiarity with real-time communication protocols: WebSockets, gRPC. Strong understanding of cloud platforms (AWS preferred) and serverless architectures. Good experience with DevOps tools: GitHub Actions, Jenkins, Terraform (optional). Bonus Skills Exposure to integrating AI/ML models (especially LLMs, STT, Diarization models) in backend systems. Familiarity with vector search databases and RAG-based architectures. Knowledge of GraphQL API development (optional). Experience in multilingual platform scaling (support for Indic languages is a plus). Preferred Qualifications Bachelor’s or Master’s degree in Computer Science, Engineering, or a related technical field. Experience working in product startups, SaaS platforms, AI-based systems, or high-growth technology companies. Proven track record of owning backend architecture at scale (millions of users or real-time systems). Strong understanding of software design principles (SOLID, DRY, KISS) and scalable system architecture. What You’ll Get Ownership : Lead backend engineering at one of India's fastest-growing GenAI startups. Impact : Build systems that directly power the world's next-generation enterprise sales platforms. Learning : Work with an elite founding team and top engineers from IIT, IIM, BITS, and top tech companies. Growth : Fast-track your career into senior technology leadership roles. Compensation : Competitive salary + ESOPs + performance bonuses. Culture : High-trust, high-ownership, no-bureaucracy environment focused on speed and innovation. Vision : Be a part of a once-in-a-decade opportunity building from India for the world. About the Tech Stack You’ll Work On Languages : Python 3.x Frameworks : FastAPI (Primary), Flask/Django (Secondary) Data Stores : PostgreSQL, MongoDB, Redis, FAISS, Pinecone Messaging Systems : Kafka, Redis Streams Cloud Platforms : AWS (EC2, S3, Lambda, EKS) DevOps : Docker, Kubernetes, GitHub Actions Others : WebSockets, OAuth 2.0, JWT, Microservices Patterns Application Process Submit your updated resume and GitHub/portfolio links (if available). Shortlisted candidates will have a technical discussion and coding assessment. Technical interview rounds covering system design, backend architecture, and problem-solving. Final leadership interaction round. Offer! How to Apply 📩 careers@darwix.ai Please include: Updated resume GitHub profile (optional but preferred) 2–3 lines about why you're excited to join Darwix AI as a Lead Backend Engineer Join Us at Darwix AI – Build the AI Future for Revenue Teams, Globally! #LeadBackendDeveloper #PythonEngineer #MicroservicesArchitecture #BackendEngineering #FastAPI #DarwixAI #AIStartup #TechCareers

🧠 Job Title: Senior Machine Learning Engineer Company : Darwix AI Location : Gurgaon (On-site) Type : Full-Time Experience : 4–8 years Education : B.Tech / M.Tech / Ph.D. in Computer Science, Machine Learning, Artificial Intelligence, or related fields 🚀 About Darwix AI Darwix AI is India's fastest-growing GenAI SaaS startup, building real-time conversational intelligence and agent-assist platforms that supercharge omnichannel enterprise sales teams across India, MENA, and Southeast Asia. Our mission is to redefine how revenue teams operate by using Generative AI, LLMs, Voice AI , and deep analytics to deliver better conversations, faster deal cycles, and consistent growth. Our flagship platform, Transform+ , analyzes millions of hours of sales conversations, gives live nudges, builds AI-powered sales content, and enables revenue teams to become truly data-driven — in real time. We’re backed by marquee investors, industry veterans, and AI experts, and we’re expanding fast. As a Senior Machine Learning Engineer , you will play a pivotal role in designing and deploying intelligent ML systems that power every layer of this platform — from speech-to-text, diarization, vector search, and summarization to recommendation engines and personalized insights. 🎯 Role Overview This is a high-impact, high-ownership role for someone who lives and breathes data, models, and real-world machine learning. You will design, train, fine-tune, deploy, and optimize ML models across various domains — speech, NLP, tabular, and ranking. Your work will directly power critical product features: from personalized agent nudges and conversation scoring to lead scoring, smart recommendations, and retrieval-augmented generation (RAG) pipelines. You’ll be the bridge between data science, engineering, and product — converting ideas into models, and models into production-scale systems with tangible business value. 🧪 Key Responsibilities🔬 1. Model Design, Training, and Optimization Develop and fine-tune machine learning models using structured, unstructured, and semi-structured data sources. Work with models across domains: text classification, speech transcription, named entity recognition, topic modeling, summarization, time series, and recommendation systems. Explore and implement transformer architectures, BERT-style encoders, Siamese networks, and retrieval-based models. 📊 2. Data Engineering & Feature Extraction Build robust ETL pipelines to clean, label, and enrich data for supervised and unsupervised learning tasks. Work with multimodal inputs — audio, text, metadata — and build smart representations for downstream tasks. Automate data collection from APIs, CRMs, sales transcripts, and call logs. ⚙️ 3. Productionizing ML Pipelines Package and deploy models in scalable APIs (using FastAPI, Flask, or similar frameworks). Work closely with DevOps to containerize and orchestrate ML workflows using Docker, Kubernetes, or CI/CD pipelines. Ensure production readiness: logging, monitoring, rollback, and fail-safes. 📈 4. Experimentation & Evaluation Design rigorous experiments using A/B tests, offline metrics, and post-deployment feedback loops. Continuously optimize model performance (latency, accuracy, precision-recall trade-offs). Implement drift detection and re-training pipelines for models in production. 🔁 5. Collaboration with Product & Engineering Translate business problems into ML problems and align modeling goals with user outcomes. Partner with product managers, AI researchers, data annotators, and frontend/backend engineers to build and launch features. Contribute to the product roadmap with ML-driven ideas and prototypes. 🛠️ 6. Innovation & Technical Leadership Evaluate open-source and proprietary LLM APIs, AutoML frameworks, vector databases, and model inference techniques. Drive innovation in voice-to-insight systems (ASR + Diarization + NLP). Mentor junior engineers and contribute to best practices in ML development and deployment. 🧰 Tech Stack🔧 Languages & Frameworks Python (core), SQL, Bash PyTorch, TensorFlow, HuggingFace, scikit-learn, XGBoost, LightGBM 🧠 ML & AI Ecosystem Transformers, RNNs, CNNs, CRFs BERT, RoBERTa, GPT-style models OpenAI API, Cohere, LLaMA, Mistral, Anthropic Claude FAISS, Pinecone, Qdrant, LlamaIndex ☁️ Deployment & Infrastructure Docker, Kubernetes, GitHub Actions, Jenkins AWS (EC2, Lambda, S3, SageMaker), GCP, Azure Redis, PostgreSQL, MongoDB 📊 Monitoring & Experimentation MLflow, Weights & Biases, TensorBoard, Prometheus, Grafana 👨‍💼 Qualifications🎓 Education Bachelor’s or Master’s degree in CS, AI, Statistics, or related quantitative disciplines. Certifications in advanced ML, data science, or AI are a plus. 🧑‍💻 Experience 4–8 years of hands-on experience in applied machine learning. Demonstrated success in deploying models to production at scale. Deep familiarity with transformer-based architectures and model evaluation. ✅ You’ll Excel In This Role If You… Thrive on solving end-to-end ML problems — not just notebooks, but deployment, testing, and iteration. Obsess over clean, maintainable, reusable code and pipelines. Think from first principles and challenge model assumptions when they don’t work. Are deeply curious and have built multiple projects just because you wanted to know how something works. Are comfortable working with ambiguity, fast timelines, and real-time data challenges. Want to build AI products that get used by real people and drive revenue outcomes — not just vanity demos. 💼 What You’ll Get at Darwix AI Work with some of the brightest minds in AI , product, and design. Solve AI problems that push the boundaries of real-time, voice-first, multilingual enterprise use cases. Direct mentorship from senior architects and AI scientists. Competitive compensation (₹30L–₹45L CTC) + ESOPs + rapid growth trajectory. Opportunity to shape the future of a global-first AI startup built from India. Hands-on experience with the most advanced tech stack in applied ML and production AI. Front-row seat to a generational company that is redefining enterprise AI. 📩 How to Apply Ready to build with us? Send your resume, GitHub/portfolio, and a short write-up on: “What’s the most interesting ML system you’ve built — and what made it work?” Email: people@darwix.ai Subject: Senior ML Engineer – Application 🔐 Final Notes We value speed, honesty, and humility. We ship fast, fail fast, and learn even faster. This role is designed for high-agency, hands-on ML engineers who want to make a difference — not just write code. If you’re looking for a role where you own real impact , push technical boundaries, and work with a team that’s as obsessed with AI as you are — then Darwix AI is the place for you. Darwix AI – GenAI for Revenue Teams. Built from India, for the World.

🚀 Job Title: Engineering Lead Company: Darwix AI Location: Gurgaon (On-site) Type: Full-Time Experience: 5–10 Years Compensation: Competitive + Performance-based incentives + Meaningful ESOPs 🧠 About Darwix AI Darwix AI is one of India’s fastest-growing AI startups, building the future of enterprise revenue intelligence. We offer a GenAI-powered conversational intelligence and real-time agent assist suite that transforms how large sales teams interact, close deals, and scale operations. We’re already live with enterprise clients across India, the UAE, and Southeast Asia , and our platform enables multilingual speech-to-text, AI-driven nudges, and contextual conversation coaching—backed by our proprietary LLMs and cutting-edge voice infrastructure. With backing from top-tier VCs and over 30 angel investors, we’re now hiring an Engineering Lead who can architect, own, and scale the core engineering stack as we prepare for 10x growth. 🌟 Role Overview As the Engineering Lead at Darwix AI , you’ll take ownership of our platform architecture, product delivery, and engineering quality across the board. You’ll work closely with the founders, product managers, and the AI team to convert fast-moving product ideas into scalable features. You will: Lead backend and full-stack engineers across microservices, APIs, and real-time pipelines Architect scalable systems for AI/LLM deployments Drive code quality, maintainability, and engineering velocity This is a hands-on, player-coach role —perfect for someone who loves building but is also excited about mentoring and growing a technical team. 🎯 Key Responsibilities🛠️ Technical Leadership Own technical architecture across backend, frontend, and DevOps stacks Translate product roadmaps into high-performance, production-ready systems Drive high-quality code reviews, testing practices, and performance optimization Make critical system-level decisions around scalability, security, and reliability 🚀 Feature Delivery Work with the product and AI teams to build new features around speech recognition, diarization, real-time coaching, and analytics dashboards Build and maintain backend services for data ingestion, processing, and retrieval from Vector DBs, MySQL, and MongoDB Create clean, reusable APIs (REST & WebSocket) that power our web-based agent dashboards 🧱 System Architecture Refactor monoliths into microservice-based architecture Optimize real-time data pipelines with Redis, Kafka, and async queues Implement serverless modules using AWS Lambda, Docker containers, and CI/CD pipelines 🧑‍🏫 Mentorship & Team Building Lead a growing team of engineers—guide on architecture, code design, and performance tuning Foster a culture of ownership, documentation, and continuous learning Mentor junior developers, review PRs, and set up internal coding best practices 🔄 Collaboration Act as the key technical liaison between Product, Design, AI/ML, and DevOps teams Work directly with founders on roadmap planning, delivery tracking, and go-live readiness Contribute actively to investor tech discussions, client onboarding, and stakeholder calls ⚙️ Our Tech Stack Languages: Python (FastAPI, Django), PHP (legacy support), JavaScript, TypeScript Frontend: HTML, CSS, Bootstrap, Mustache templates; (React.js/Next.js optional) AI/ML Integration: LangChain, Whisper, RAG pipelines, Transformers, Deepgram, OpenAI APIs Databases: MySQL, PostgreSQL, MongoDB, Redis, Pinecone/FAISS (Vector DBs) Cloud & Infra: AWS EC2, S3, Lambda, CloudWatch, Docker, GitHub Actions, Nginx DevOps: Git, Docker, CI/CD pipelines, Jenkins/GitHub Actions, load testing Tools: Jira, Notion, Slack, Postman, Swagger 🧑‍💼 Who You Are 5–10 years of professional experience in backend/full-stack development Proven experience leading engineering projects or mentoring junior devs Comfortable working in high-growth B2B SaaS startups or product-first orgs Deep expertise in one or more backend frameworks (Django, FastAPI, Laravel, Flask) Experience working with AI products or integrating APIs from OpenAI, Deepgram, HuggingFace is a huge plus Strong understanding of system design, DB normalization, caching strategies, and latency optimization Bonus: exposure to working with voice pipelines (STT/ASR), NLP models, or real-time analytics 📌 Qualities We’re Looking For Builder-first mindset – you love launching features fast and scaling them well Execution speed – you move with urgency but don’t break things Hands-on leadership – you guide people by writing code, not just processes Problem-solver – when things break, you own the fix and the root cause Startup hunger – you thrive on chaos, ambiguity, and shipping weekly 🎁 What We Offer High Ownership : Directly shape the product and its architecture from the ground up Startup Velocity : Ship fast, learn fast, and push boundaries Founding Engineer Exposure : Work alongside IIT-IIM-BITS founders with full transparency Compensation : Competitive salary + meaningful equity + performance-based incentives Career Growth : Move into an EM/CTO-level role as the org scales Tech Leadership : Own features end-to-end—from spec to deployment 🧠 Final Note This is not just another engineering role. This is your chance to: Own the entire backend for a GenAI product serving global enterprise clients Lead technical decisions that define our future infrastructure Join the leadership team at a startup that’s shipping faster than anyone else in the category If you're ready to build a product with 10x potential, join a high-output team, and be the reason why the tech doesn’t break at scale , this role is for you. 📩 How to Apply Send your resume to people@darwix.ai with the subject line: “Application – Engineering Lead – [Your Name]” Attach: Your latest CV or LinkedIn profile GitHub/portfolio link (if available) A short note (3–5 lines) on why you're excited about Darwix AI and this role

Dreaming big is in our DNA. It’s who we are as a company. It’s our culture. It’s our heritage. And more than ever, it’s our future. A future where we’re always looking forward. Always serving up new ways to meet life’s moments. A future where we keep dreaming bigger. We look for people with passion, talent, and curiosity, and provide them with the teammates, resources and opportunities to unleash their full potential. The power we create together – when we combine your strengths with ours – is unstoppable. Are you ready to join a team that dreams as big as you do? AB InBev GCC was incorporated in 2014 as a strategic partner for Anheuser-Busch InBev. The center leverages the power of data and analytics to drive growth for critical business functions such as operations, finance, people, and technology. The teams are transforming Operations through Tech and Analytics. Do You Dream Big? We Need You. Job Description Job Title: Junior Data Scientist Location: Bangalore Reporting to: Senior Manager – Analytics Purpose of the role The Global GenAI Team at Anheuser-Busch InBev (AB InBev) is tasked with constructing competitive solutions utilizing GenAI techniques. These solutions aim to extract contextual insights and meaningful information from our enterprise data assets. The derived data-driven insights play a pivotal role in empowering our business users to make well-informed decisions regarding their respective products. In the role of a Machine Learning Engineer (MLE), you will operate at the intersection of: LLM-based frameworks, tools, and technologies Cloud-native technologies and solutions Microservices-based software architecture and design patterns As an additional responsibility, you will be involved in the complete development cycle of new product features, encompassing tasks such as the development and deployment of new models integrated into production systems. Furthermore, you will have the opportunity to critically assess and influence the product engineering, design, architecture, and technology stack across multiple products, extending beyond your immediate focus. Key tasks & accountabilities Large Language Models (LLM): Experience with LangChain, LangGraph Proficiency in building agentic patterns like ReAct, ReWoo, LLMCompiler Multi-modal Retrieval-Augmented Generation (RAG): Expertise in multi-modal AI systems (text, images, audio, video) Designing and optimizing chunking strategies and clustering for large data processing Streaming & Real-time Processing: Experience in audio/video streaming and real-time data pipelines Low-latency inference and deployment architectures NL2SQL: Natural language-driven SQL generation for databases Experience with natural language interfaces to databases and query optimization API Development: Building scalable APIs with FastAPI for AI model serving Containerization & Orchestration: Proficient with Docker for containerized AI services Experience with orchestration tools for deploying and managing services Data Processing & Pipelines: Experience with chunking strategies for efficient document processing Building data pipelines to handle large-scale data for AI model training and inference AI Frameworks & Tools: Experience with AI/ML frameworks like TensorFlow, PyTorch Proficiency in LangChain, LangGraph, and other LLM-related technologies Prompt Engineering: Expertise in advanced prompting techniques like Chain of Thought (CoT) prompting, LLM Judge, and self-reflection prompting Experience with prompt compression and optimization using tools like LLMLingua, AdaFlow, TextGrad, and DSPy Strong understanding of context window management and optimizing prompts for performance and efficiency Qualifications, Experience, Skills Level of educational attainment required (1 or more of the following) Bachelor's or masterʼs degree in Computer Science, Engineering, or a related field. Previous Work Experience Required Proven experience of 1+ years in developing and deploying applications utilizing Azure OpenAI and Redis as a vector database. Technical Skills Required Solid understanding of language model technologies, including LangChain, OpenAI Python SDK, LammaIndex, OLamma, etc. Proficiency in implementing and optimizing machine learning models for natural language processing. Experience with observability tools such as mlflow, langsmith, langfuse, weight and bias, etc. Strong programming skills in languages such as Python and proficiency in relevant frameworks. Familiarity with containerization and orchestration tools (e.g., Docker, Kubernetes). And above all of this, an undying love for beer! We dream big to create future with more cheer

Avant de postuler à un emploi, sélectionnez votre langue de préférence parmi les options disponibles en haut à droite de cette page. Découvrez votre prochaine opportunité au sein d'une organisation qui compte parmi les 500 plus importantes entreprises mondiales. Envisagez des opportunités innovantes, découvrez notre culture enrichissante et travaillez avec des équipes talentueuses qui vous poussent à vous développer chaque jour. Nous savons ce qu’il faut faire pour diriger UPS vers l'avenir : des personnes passionnées dotées d’une combinaison unique de compétences. Si vous avez les qualités, de la motivation, de l'autonomie ou le leadership pour diriger des équipes, il existe des postes adaptés à vos aspirations et à vos compétences d'aujourd'hui et de demain. Fiche De Poste Job Title: Intermediate Data Developer – Azure ADF and Databricks Experience Range: 5-7 Years Location: Chennai, Hybrid Employment Type: Full-Time About UPS UPS is a global leader in logistics, offering a broad range of solutions that include transportation, distribution, supply chain management, and e-commerce. Founded in 1907, UPS operates in over 220 countries and territories, delivering packages and providing specialized services worldwide. Our mission is to enable commerce by connecting people, places, and businesses, with a strong focus on sustainability and innovation. About UPS Supply Chain Symphony™ The UPS Supply Chain Symphony™ platform is a cloud-based solution that seamlessly integrates key supply chain components, including shipping, warehousing, and inventory management, into a unified platform. This solution empowers businesses by offering enhanced visibility, advanced analytics, and customizable dashboards to streamline global supply chain operations and decision-making. About The Role We are seeking an experienced Senior Data Developer to join our data engineering team responsible for building and maintaining complex data solutions using Azure Data Factory (ADF), Azure Databricks , and Cosmos DB . The role involves designing and developing scalable data pipelines, implementing data transformations, and ensuring high data quality and performance. The Senior Data Developer will work closely with data architects, testers, and analysts to deliver robust data solutions that support strategic business initiatives. The ideal candidate should possess deep expertise in big data technologies, data integration, and cloud-native data engineering solutions on Microsoft Azure. This role also involves coaching junior developers, conducting code reviews, and driving strategic improvements in data architecture and design patterns. Key Responsibilities Data Solution Design and Development: Design and develop scalable and high-performance data pipelines using Azure Data Factory (ADF). Implement data transformations and processing using Azure Databricks. Develop and maintain NoSQL data models and queries in Cosmos DB. Optimize data pipelines for performance, scalability, and cost efficiency. Data Integration and Architecture: Integrate structured and unstructured data from diverse data sources. Collaborate with data architects to design end-to-end data flows and system integrations. Implement data security, governance, and compliance standards. Performance Tuning and Optimization: Monitor and tune data pipelines and processing jobs for performance and cost efficiency. Optimize data storage and retrieval strategies for Azure SQL and Cosmos DB. Collaboration and Mentoring: Collaborate with cross-functional teams including data testers, architects, and business analysts. Conduct code reviews and provide constructive feedback to improve code quality. Mentor junior developers, fostering best practices in data engineering and cloud development. Primary Skills Data Engineering: Azure Data Factory (ADF), Azure Databricks. Cloud Platform: Microsoft Azure (Data Lake Storage, Cosmos DB). Data Modeling: NoSQL data modeling, Data warehousing concepts. Performance Optimization: Data pipeline performance tuning and cost optimization. Programming Languages: Python, SQL, PySpark Secondary Skills DevOps and CI/CD: Azure DevOps, CI/CD pipeline design and automation. Security and Compliance: Implementing data security and governance standards. Agile Methodologies: Experience in Agile/Scrum environments. Leadership and Mentoring: Strong communication and coaching skills for team collaboration. Soft Skills Strong problem-solving abilities and attention to detail. Excellent communication skills, both verbal and written. Effective time management and organizational capabilities. Ability to work independently and within a collaborative team environment. Strong interpersonal skills to engage with cross-functional teams. Educational Qualifications Bachelor's degree in Computer Science, Engineering, Information Technology, or a related field. Relevant certifications in Azure and Data Engineering, such as: Microsoft Certified: Azure Data Engineer Associate Microsoft Certified: Azure Solutions Architect Expert Databricks Certified Data Engineer Associate or Professional About The Team As a Senior Data Developer , you will be working with a dynamic, cross-functional team that includes developers, product managers, and other quality engineers. You will be a key player in the quality assurance process, helping shape testing strategies and ensuring the delivery of high-quality web applications. Type De Contrat en CDI Chez UPS, égalité des chances, traitement équitable et environnement de travail inclusif sont des valeurs clefs auxquelles nous sommes attachés.

We are excited to share a fantastic opportunity for the AI Lead/Sr. AI-ML Engineer position at Gritstone Technologies . We believe your skills and experience could be a perfect match for this role, and we would love for you to explore this opportunity with us. Design and implement scalable, high-performance AI/ML architectures with Python tailored for real-time and batch processing use cases. Lead the development of robust, end-to-end AI pipelines, including advanced data preprocessing, feature engineering, model development, and deployment. Define and drive the integration of AI solutions across cloud-native platforms (AWS, Azure, GCP) with optimized cost-performance trade-offs. Architect and deploy multimodal AI systems, leveraging advanced NLP (e.g., LLMs, OpenAI-based customizations, scanned invoice data extraction), computer vision (e.g., inpainting, super-resolution scaling, video-based avatar generation), and generative AI technologies (e.g., video and audio generation). Integrate domain-specific AI solutions, such as reinforcement learning, and self-supervised learning models. Implement distributed training and inferencing pipelines using state-of-the-art frameworks. Drive model optimization through quantization, pruning, sparsity techniques, and mixed-precision training to maximize performance across GPU hardware. Develop scalable solutions using large vision-language models (VLMs) and large language models (LLMs). Define and implement MLOps practices for version control, CI/CD pipelines, and automated model deployment using tools like Kubernetes, Docker, Kubeflow, and FastAPI. Enable seamless integration of databases (SQL Server, MongoDB, NoSQL) with AI workflows. Drive cutting-edge research in AI/ML, including advancements in RLHF, retrieval-augmented generation (RAG), and multimodal knowledge graphs. Experiment with emerging generative technologies, such as diffusion models for video generation and neural audio synthesis. Collaborate with cross-functional stakeholders to deliver AI-driven business solutions aligned with organizational goals. null 5+ years of Experience

The AIN QA Technical Resource Team Senior Manager will play a critical role in advancing Quality Assurance initiatives across the Quality Operations Network, with a particular focus on leading and directing a team of quality professionals responsible for the support of Management Review, Inspections and Compliance, and Technical Writing & Data Analytics. The senior manager will use strategic planning and prioritization to support the collective requirements of the Quality organization alongside the individual needs and timelines of the sites. The individual will be required to work from our office located in Hyderabad India (Amgen India-AIN). The candidate will also lead the remote support from AIN to Amgen sites across multiple time zones globally This candidate will primarily work during regular working hours (9 am – 6 PM local time) to enable the business in delivering Amgen’s mission to serve patients and may lead a shift-based team that provides coverage in support of the Amgen network across multiple time zones. The candidate may need to work outside of his/her routine workday to support business needs and will be responsible for determining the same for their staff. As Senior Manager in the Quality Assurance organization, you’re in a leadership position with responsibilities to supervise and mentor staff. As a leader, you will focus your efforts on the following functions in support of global Quality Assurance operations: Focus Areas This role provides operational support, technical leadership, and cross-functional collaboration to ensure compliance, continuous improvement, and data-driven decision making in support of the Quality Management System (QMS). Oversight of the AIN-based Quality Assurance Technical Resource team Collaboration with the global quality leaders and business process owner(s) to resolve issues encountered by the team Management of request prioritization in alignment with QA network needs Support staff training, career development and performance management of team across all three shifts Responsible for ensuring compliance with safety guidelines, cGMPs and other applicable regulatory requirements Champion process improvements to increase efficiency and productivity Assign workload appropriately and strategically based on required interactions with sites in the Amgen network across multiple time zones The following are some examples of tasks for the position Support of management review (MR) at each Amgen site through collaboration with Amgen leadership and coordination of the AIN technical support team to provide MR (management review) logistical support, metrics/KPI’s, meeting agenda/content, site-level and cross-site trend analysis, and meeting facilitation. Leading the team responsible to provide readiness and response for internal and external inspections, including generation of pre-inspection documents such as deviation lists, change controls, and supporting evidence. Actively contribute during inspections by managing team to provide timely response to information requests, facilitating document electronic retrieval, and preparing responses in collaboration with subject matter experts. Leading a technical writing and data analytics workstream that includes responsibility for periodic quality trend report authorship, Site Master File authoring, product and process monitoring deviation summary reports, and leading quality risk management processes. Preferred Qualifications Strong project management skills and experience supervising professionals in a Quality organization working with cross functional and global stakeholders across multiple time zones Working knowledge of cGMP regulations Excellent written and verbal communication skills, ability to work in a team environment and build relationships with partners Track record of building and maintaining a high performing team Experience with various Quality Systems and applications Strong leadership and negotiation skills with a demonstrated ability to influence others Demonstrated innovative thinking and ability to transform work organizations Demonstrated ability to navigate through ambiguity and provide structured problem solving Demonstrated ability to deliver right the first time on schedule in accordance with established Service Level Agreements Demonstrated skills in staff motivation, coaching/mentoring and professional development Basic Qualifications and Experience: Master’s degree with 12-16 years of Pharma and Biotech commercial or clinical manufacturing Quality experience.

QA Technical Specialist The AIN QA Technical Specialist plays a critical role in advancing Quality Assurance initiatives across the Quality Operations Network, with a particular focus on Management Review, Inspections and Compliance, and Technical Writing & Data Analytics. This role provides operational support, technical leadership, and cross-functional collaboration to ensure compliance, continuous improvement, and data-driven decision making in support of the Quality Management System (QMS). The position will be responsible for tasks including the key responsibilities documented below and other technical quality-related job functions. This candidate will primarily work during regular working hours (9 AM – 6 PM local time) to enable the business in delivering Amgen’s mission to serve patients and may lead a shift-based team that provides coverage in support of the Amgen network across multiple time zones. The candidate may need to work outside of his/her routine workday to support business needs and will be responsible for determining the same for their staff. The individual will be required to work from our office located in Hyderabad India (Amgen India-AIN). The candidate will also lead the remote support from AIN to Amgen sites globally. Key Responsibilities - Management Review Coordinate and manage all logistics related to Site Management Review, including compiling metrics, maintaining and updating Smartsheet trackers, and preparing content. Perform site-level and cross-site trend analysis (as applicable) using key quality metrics; identify trends and collaborate with site stakeholders to implement corrective and preventive actions (CAPA). Lead preparation of Management Review meetings, ensuring comprehensive data presentation creation, documentation of meeting minutes, and follow-up on action items. Inspections and Compliance Support readiness and response for internal and external inspections, including generation of pre-inspection documents such as deviation lists, change controls, and supporting evidence. Actively contribute during inspections by managing information requests, facilitating document electronic retrieval, and preparing responses in collaboration with subject matter experts. Lead Site Master File updates by coordinating content input from cross-functional stakeholders, drafting revisions, and managing review and approval workflows. Technical Writing and Data Analytics Lead authoring and workflow coordination for periodic quality trend reports and related documentation. Generate deviation summary reports to support product and process monitoring efforts, ensuring accuracy and consistency with cGMP standards. Drive quality risk assessments, providing technical leadership in risk identification, analysis, and mitigation planning in alignment with standards. Preferred Qualifications Demonstrated experience in a GMP-compliant environment with working knowledge of inspection protocols, site audits, and quality risk management principles. Proficiency in technical writing and data visualization tools; experience with Smartsheet, Tableau, or equivalent platforms preferred. Strong analytical skills with the ability to interpret data trends and drive improvements based on quality insights. Familiarity with electronic quality systems (e.g., Veeva, TrackWise, SAP-QM, LIMS) and documentation practices. Excellent verbal and written communication skills, including experience presenting to senior leaders. Proven ability to lead and collaborate within cross-functional teams in a dynamic, fast-paced setting. Core Competencies Leadership in Quality Governance (e.g., Management Review) Inspection Readiness and Compliance Assurance Quality Data Visualization, Interpretation and Analytics Technical Document Drafting and Workflow Ownership Cross-Functional Stakeholder Engagement Continuous Improvement Mindset Basic Qualifications and Experience: Master’s degree with 8-13 years of Pharma and Biotech commercial or clinical manufacturing Quality experience.

Description Company Overview: When it comes to IT solution providers, there are a lot of choices. But when it comes to providers with innovative and differentiating end-to-end service offerings, there’s really only one: Zones – First Choice for IT.TM Zones is a Global Solution Provider of end-to-end IT solutions with an unmatched supply chain. Positioned to be the IT partner you need, Zones, a Minority Business Enterprise (MBE) in business for over 35 years, specializes in Digital Workplace, Cloud & Data Center, Networking, Security, and Managed/Professional/Staffing services. Operating in more than 120 countries, leveraging a robust portfolio, and utilizing the highest certification levels from key partners, including Microsoft, Apple, Cisco, Lenovo, Adobe, and more, Zones has mastered the science of building digital infrastructures that change the way business does business ensuring whatever they need, they can Consider IT Done. Follow Zones, LLC on Twitter @Zones, and LinkedIn and Facebook. Position Overview: The primary focus of this position is to Design, develop, and maintain robust data pipelines using Azure Data Factory. Implement and manage ETL processes to ensure efficient data flow and transformation. What you’ll do as a (BI Developer Lead): Design, develop, and maintain robust data pipelines using Azure Data Factory. Implement and manage ETL processes to ensure efficient data flow and transformation. Develop and maintain data models and data warehouses using Azure SQL Database and Azure Synapse Analytics. Create and manage Power BI reports and dashboards to provide actionable insights to stakeholders. Ensure data quality, integrity, and security across all data systems. Collaborate with cross-functional teams to understand data requirements and deliver solutions. Optimize data storage and retrieval processes for performance and cost efficiency. Monitor and troubleshoot data pipelines and workflows to ensure smooth operations. Create and maintain tabular models for efficient data analysis and reporting. Stay updated with the latest Azure services and best practices to continuously improve data infrastructure. What will you bring to the team: Bachelor’s degree in computer science, Information Technology, or a related field. Certification in Azure Data Engineer or related Azure certifications will be an added advantage. Experience with machine learning and AI services on Azure will be an added advantage. Proven experience in designing and maintaining data pipelines using Azure Data Factory. Strong proficiency in SQL and experience with Azure SQL Database. Hands-on experience with Azure Synapse Analytics and Azure Data Lake Storage. Proficiency in creating and managing Power BI reports and dashboards. Knowledge of Azure DevOps for CI/CD pipeline implementation. Strong problem-solving skills and attention to detail. Excellent communication and collaboration skills. Knowledge of data governance and compliance standards. Zones offers a comprehensive Benefits package. While we’re committed to providing top-tier solutions, we’re just as committed to supporting our own teams. We offer a competitive compensation package where our team members are rewarded based on their performance and recognized for the value, they bring into our business. Our team members enjoy a variety of comprehensive benefits, including Medical Insurance Coverage, Group Term Life and Personal Accident Cover to handle the uncertainties of life, flexible leave policy to balance their work life. At Zones, work is more than a job – it's an exciting careers immersed in an inventive, collaborative culture. If you’re interested in working on the cutting edge of IT innovation, sales, engineering, operations, administration, and more, Zones is the place for you! All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, veteran status or on the basis of disability.