2024 Inference Jobs - Page 35

Job Title: Voice Processing Specialist Location: Remote /Jaipur Job Type: Full-time / Contract Experience: 3+ years expertise in voice cloning, transformation, and synthesis technologies Job Summary We are seeking a talented and motivated Voice Processing Specialist to join our team and lead the development of innovative voice technologies. The ideal candidate will have a deep understanding of speech synthesis, voice cloning, and transformation techniques. You will play a critical role in designing, implementing, and deploying state-of-the-art voice models that enhance naturalness, personalization, and flexibility of speech in AI-powered applications. This role is perfect for someone passionate about advancing human-computer voice interaction and creating lifelike, adaptive voice systems. Key Responsibilities Design, develop, and optimize advanced deep learning models for voice cloning, text-to-speech (TTS), voice conversion, and real-time voice transformation. Implement speaker embedding and voice identity preservation techniques to support accurate and high-fidelity voice replication. Work with large-scale and diverse audio datasets, including preprocessing, segmentation, normalization, and data augmentation to improve model generalization and robustness. Collaborate closely with data scientists, ML engineers, and product teams to integrate developed voice models into production pipelines. Fine-tune neural vocoders and synthesis architectures for better voice naturalness and emotional range. Stay current with the latest advancements in speech processing, AI voice synthesis, and deep generative models through academic literature and open-source projects. Contribute to the development of tools and APIs for deploying models on cloud and edge environments with high efficiency and low latency. Required Skills Strong understanding of speech signal processing, speech synthesis, and automatic speech recognition (ASR) systems. Hands-on experience with voice cloning frameworks such as Descript Overdub, Coqui TTS, SV2TTS, Tacotron, FastSpeech, or similar. Proficiency in Python and deep learning frameworks like PyTorch or TensorFlow. Experience working with speech libraries and toolkits such as ESPnet, Kaldi, Librosa, or SpeechBrain. In-depth knowledge of mel spectrograms, vocoder architectures (e.g., WaveNet, HiFi-GAN, WaveGlow), and their role in speech synthesis. Familiarity with REST APIs, model deployment, and cloud-based inference systems using platforms like AWS, Azure, or GCP. Ability to optimize models for performance in real-time or low-latency environments. Preferred Qualifications Experience in real-time voice transformation, including pitch shifting, timing modification, or emotion modulation. Exposure to emotion-aware speech synthesis, multilingual voice models, or prosody modeling. Design, develop, and optimize advanced deep learning models for voice cloning, text-to-speech (TTS), voice conversion, and real-time voice transformation Background in audio DSP (Digital Signal Processing) and speech analysis techniques. Previous contributions to open-source speech AI projects or publications in relevant domains. Why Join Us You will be part of a fast-moving, collaborative team working at the forefront of voice AI innovation. This role offers the opportunity to make a significant impact on products that reach millions of users, helping to shape the future of interactive voice experiences. Skills: automatic speech recognition (asr),vocoder architectures,voice cloning,voice processing,data,real-time voice transformation,speech synthesis,pytorch,tensorflow,voice conversion,speech signal processing,audio dsp,rest apis,python,cloud deployment,transformation,mel spectrograms,deep learning

Job Description Function, Responsibility Level Insurance Operations, Senior Executive Reports to Assistant Manager/Lead Assistant Manager/Manager – Insurance Operations Basic Function (Property Survey) Responsible for carrying out review of property survey reports submitted by Independent Consultants (ICs) and various other tasks in a manner that is consistent with company policies, procedures and standards. Follow appropriate Operating procedure Meet quality goals Meet office time service goals Monitor e-mails, and respond in a timely manner Send reports to clients Handle additional duties as assigned Competencies Excellent written communication skills, with an ability to think and react to situations confidently Domain experience in Homeowner/ Commercial Insurance (Preferred but not mandatory) Must be assertive, persistent, and result-oriented, ability to work in a team environment and adhere to department guidelines Knowledgeable in Microsoft Word, Excel and Power Point Skills Requirement Technical Skills (Minimum) Proficient with computer systems and software including Microsoft Excel, Outlook and Word Typing Speed of at least 30 WPM and 90% accuracy Soft Skills (Minimum) Good Communication Skills – Able to express thoughts and ideas in an accurate and understandable manner through verbal and written format with internal and external contacts High Levels of Comprehension – Able to understand and follow information received from field staff or from the customer Able to identify the main idea, cause and effect, fact and opinion, make inference, compare and contrast, sequence information, and draw conclusions basis the information acquired or provided Customer Focus Identifies and understands the (internal or external) customer’s needs Detail oriented with excellent follow up skills Teamwork Works effectively with the team to accomplish goals, takes action that respects the needs of others and those of the organization Effective interpersonal skills Adaptability Maintains effectiveness despite changes to situations, tasks, responsibilities, and people Professionalism Conducting oneself with responsibility, integrity, accountability and excellence Work Standards Sets own high standards of performance Education Requirements Minimum of bachelor’s degree in any field Work Experience Requirements Minimum 1 year of work experience in BPO preferably in P&C Insurance

Location: IN - Hyderabad Telangana Goodyear Talent Acquisition Representative: Ashutosh Panda Sponsorship Available: No Relocation Assistance Available: No Job Description Roles and Responsibilties : Analyze, design and develop new processes, programs and configuration - Taking into account the complex inter-relationships of system-wide components Provide system-wide support and maintenance for a complex system or business process. Maintain and modify existing processes, programs and configuration through use of current IT Toolsets. Troubleshoot, investigate and persist. Develop solutions to problems with unknown causes where precedents do not exist, by applying logic and inference with persistence and experience to see the problem through to resolution. Confer with the stakeholder community on problem determination. Make joint analysis decisions on cause and correction methods. Perform tasks (as necessary) to ensure data integrity and system stability. Complete life-cycle testing (unit and integration) of all work processes (including Cross Platform Interaction). Create applications and databases with main focus on Data Collection Systems - Supporting Analysis, Data Capture, Design Tools, Library Functions, Reporting, Request Systems and Specification Systems used in the Tire Development Process. Knowlege,Skills,Abilities : Developing an understanding of skills needed in other disciplines, of second business process area and basic Cost/Benefit Analysis Method. 3+ Years of strong development experience with Java and Springboot. 3+ Years of strong experience of working with cloud based environment(AWS - Event Driven Architecture). Strong experience of working with Microservices & SQL Server. Good to have some knowledge on Salesforce application. Basic Organizational, Communication and Time Management skills Participate as an active Team Member (Effective Listening and Collaboration skills) Achieve all IT Objectives through use of approved Standards and Guidelines Goodyear is an Equal Employment Opportunity and Affirmative Action Employer. All qualified applicants will receive consideration for employment without regard to that individual's race, color, religion or creed, national origin or ancestry, sex (including pregnancy), sexual orientation, gender identity, age, physical or mental disability, ethnicity, citizenship, or any other characteristic protected by law. Goodyear is one of the world’s largest tire companies. It employs about 68,000 people and manufactures its products in 53 facilities in 20 countries around the world. Its two Innovation Centers in Akron, Ohio and Colmar-Berg, Luxembourg strive to develop state-of-the-art products and services that set the technology and performance standard for the industry. For more information about Goodyear and its products, go to www.goodyear.com/corporate #Li-Hybrid

About Celestial AI As Generative AI continues to advance, the performance drivers for data center infrastructure are shifting from systems-on-chip (SOCs) to systems of chips. In the era of Accelerated Computing, data center bottlenecks are no longer limited to compute performance, but rather the system's interconnect bandwidth, memory bandwidth, and memory capacity. Celestial AI's Photonic Fabric™ is the next-generation interconnect technology that delivers a tenfold increase in performance and energy efficiency compared to competing solutions. The Photonic Fabric™ is available to our customers in multiple technology offerings, including optical interface chiplets, optical interposers, and Optical Multi-chip Interconnect Bridges (OMIB). This allows customers to easily incorporate high bandwidth, low power, and low latency optical interfaces into their AI accelerators and GPUs. The technology is fully compatible with both protocol and physical layers, including standard 2.5D packaging processes. This seamless integration enables XPUs to utilize optical interconnects for both compute-to-compute and compute-to-memory fabrics, achieving bandwidths in the tens of terabits per second with nanosecond latencies. This innovation empowers hyperscalers to enhance the efficiency and cost-effectiveness of AI processing by optimizing the XPUs required for training and inference, while significantly reducing the TCO2 impact. To bolster customer collaborations, Celestial AI is developing a Photonic Fabric ecosystem consisting of tier-1 partnerships that include custom silicon/ASIC design, system integrators, HBM memory, assembly, and packaging suppliers. ABOUT THE ROLE Celestial AI is looking for a highly motivated and detail-oriented Software Quality Assurance (SQA) Manager to join our team. As an SQA Manager, you will lead a small team of engineers and play a critical role in ensuring the quality of our software products. You will be responsible for managing the team, as well as designing, developing, and executing test plans and test cases, identifying and reporting defects, and working closely with developers to ensure that our software meets the highest standards. This is a hands-on leadership position that requires both technical depth and leadership skills. ESSENTIAL DUTIES AND RESPONSIBILITIES Test Strategy & Planning: Develop comprehensive test plans, strategies, and methodologies specifically tailored for embedded firmware, covering functional, non-functional (performance, power, memory), reliability, stress, and security aspects. Test Case Design & Execution: Design, document, and execute detailed test cases for firmware components, drivers, communication protocols, and system-level interactions with hardware. Hardware-Firmware Integration Testing: Lead and perform testing at the hardware-firmware interface, ensuring seamless and correct interaction between embedded software and physical components (e.g., sensors, actuators, external memory, peripherals like SPI, I2C, UART). Automation Development: Design, develop, and maintain automated test scripts and test harnesses using scripting languages (e.g., Python, Bash) and specialized tools to enhance test coverage and efficiency, particularly for regression testing. Defect Management: Identify, document, track, and verify resolution of software defects using bug tracking systems. Provide clear and concise bug reports with steps to reproduce and relevant logs. Root Cause Analysis: Collaborate with firmware developers to perform in-depth root cause analysis of defects, often involving debugging on embedded targets using JTAG/SWD, oscilloscopes, logic analyzers, and other hardware debugging tools. Performance & Resource Analysis: Monitor and analyze firmware performance metrics (CPU usage, memory footprint, power consumption, boot time, latency) and validate against specified requirements. Regression & Release Qualification: Own the regression testing process and contribute significantly to the final release qualification of firmware builds. Process Improvement: Champion and contribute to the continuous improvement of firmware development and quality assurance processes, methodologies, and best practices. QUALIFICATIONS Bachelor's degree in Electrical Engineering, Computer Engineering, Computer Science, or a related technical field. 10 years of experience in Software Quality Assurance, with a minimum of 5 years directly focused on firmware or embedded software testing . Strong understanding of embedded systems concepts , including microcontrollers/microprocessors, real-time operating systems (RTOS), interrupts, memory management, and common peripheral interfaces (GPIO, I2C, SPI, UART, ADC, DAC, Timers). Proficiency in C/C++ for embedded development, with the ability to read, understand, and debug firmware code. Experience with scripting languages for test automation (e.g., Python, Bash). Hands-on experience with hardware debugging tools such as JTAG/SWD debuggers, oscilloscopes, logic analyzers, and multimeters. Familiarity with version control systems (e.g., Git) and bug tracking tools (e.g., Jira, Azure DevOps). Experience with test management tools (e.g., TestRail, Zephyr). Excellent problem-solving skills, with a methodical and analytical approach to identifying and isolating defects. PREFERRED QUALIFICATIONS Experience with continuous integration/continuous deployment (CI/CD) pipelines for embedded systems. Knowledge of networking protocols (TCP/IP) Experience with Hardware-in-the-Loop (HIL) testing, simulation, or emulation environments. LOCATION : Hyderabad, India We offer great benefits (health, vision, dental and life insurance), collaborative and continuous learning work environment, where you will get a chance to work with smart and dedicated people engaged in developing the next generation architecture for high performance computing. Celestial AI Inc. is proud to be an equal opportunity workplace and is an affirmative action employer. #LI-Onsite

At American Express, our culture is built on a 175-year history of innovation, shared values and Leadership Behaviors, and an unwavering commitment to back our customers, communities, and colleagues. As part of Team Amex, you'll experience this powerful backing with comprehensive support for your holistic well-being and many opportunities to learn new skills, develop as a leader, and grow your career. Here, your voice and ideas matter, your work makes an impact, and together, you will help us define the future of American Express. How will you make an impact in this role? Enterprise Essentials team within Financial Data Engineering is hiring for a highly skilled Senior Engineering Manager with expertise in Python/Java Full Stack Development, Generative AI, Data Engineering, and Natural Language Processing. The Senior Engineering Manager will be working on creating new capabilities and modernizing existing ones in the domain of Global Tax, Finance and GSM Conversational AI platforms, and Enterprise essential products like Reconciliations, ERRM, Balancing and Control, Concur, and Ariba. The ideal candidate will be responsible for designing, developing, and maintaining scalable AI-driven applications and data pipelines. This role requires a deep understanding of NLP techniques, modern AI frameworks, data engineering best practices, and full-stack development to build innovative solutions that leverage machine learning and AI technologies. Key Responsibilities: Oversees and mentors a team of Software Engineering colleagues, enabling a culture of continuous learning, growth opportunities, and inclusivity for all individual colleagues and teams. Provides direct leadership and coaching to teams, supporting training and development of best practices. Manages resource allocation, project timeline, and budget for Software Engineering projects, ensuring alignment with organizational goals. Collaborates with senior leadership to hire top talent for the team, ensuring a high-functioning and cohesive unit, implementing strategies for talent retention and professional development Leads the development, deployment, support, and monitoring of software across various environments. Collaborates with senior leadership and cross-functional teams to define and implement technology roadmaps and strategies. Leads teams to innovate and automate processes, driving efficiency and scalability in production environments. Drives continuous improvement initiatives, leveraging metrics and feedback to improve team performance and software quality. Collaborates and co-creates effectively with teams in product and the business to align technology initiatives with business objectives. Full Stack Development: Design and develop scalable and secure applications using Java / Python framework, and front-end technologies such as React. Implement and optimize microservices, APIs, and server-side logic for AI-based platforms. Develop and maintain cloud-based, containerized applications (Docker, Kubernetes). Design, optimize, and deploy high-performance systems ensuring minimal latency and maximum throughput. Architect solutions for real-time processing, ensuring low-latency data retrieval and high system availability. Troubleshoot and enhance system performance, optimizing for large-scale, real-time, distributed and COTS applications. Generative AI & Machine Learning: Develop, and deploy innovative solutions in Tax, and finance using ML & Generative AI models leveraging frameworks such as langchain. Implement NLP algorithms for language understanding, text summarization, information extraction, and conversational agents. Create pipelines for training and deploying AI models efficiently in production environments. Collaborate with data scientists to optimize and scale AI/NLP solutions. Integrate AI/ML models into applications, ensuring proper scaling, optimization, and monitoring of models in production. Design solutions that enable fast and efficient inference for real-time AI applications. Data Engineering: Build and maintain data pipelines to support AI/ML model development and deployment. Design and develop ETL processes to ingest, clean, and process large-scale structured and unstructured datasets. Work with data storage and retrieval solutions like SQL/NoSQL databases, data lakes, and cloud storage (GCP, AWS, or Azure). Ensure data integrity, security, and performance of the data pipelines. Collaboration & Leadership: Lead cross-functional teams to deliver high-quality, AI-driven products. Lead and mentor engineers and collaborate with product managers, data scientists, and business stakeholders to ensure alignment with project goals. Keep up-to-date with the latest advancements in AI, NLP, and data engineering, and provide technical guidance to the team. Takes accountability for the success of the team achieving their goals Drives the team’s strategy and prioritizes initiatives Influence team members by challenging status quo, demonstrating risk taking, and implementing creative ideas. Be a productivity multiplier for your team by analysing your workflow and contributing to enable the team to be more effective, productive, and demonstrating faster and stronger results. Mentor and guide team members to success within the team Minimum Qualifications Education: Bachelor’s or Master’s in Computer Science, Engineering, Data Science, or a related field. 10+ years of experience in software engineering in architecture and design (architecture, design patterns, reliability and scaling) of new and existing systems. Strong experience in developing full stack software in Java or Python, data engineering, and AI/NLP solutions and demonstrated ability to quickly learn new languages. Following standard Engineering excellence standards while building software. Leveraging code assistants like Github Copilot. Writing great prompts for generating high quality code, tests, and other artefacts like documentation. Proficiency in data engineering tools and frameworks like GCP BigQuery, Apache Spark, Kafka. Proficiency with containerization (Docker, Kubernetes), CI/CD pipelines, and version control. Experience with RESTful API design, microservices architecture, and cloud platforms (AWS / GCP / Azure). Preferred Qualifications Experience working with large-scale AI systems in production environments. Familiarity with modern AI research and developments in Generative AI and NLP. `Strong understanding of DevOps and Infrastructure-as-Code (Terraform, Ansible). Proven track record of delivering AI-driven products that scale Understanding of MLOps practices will be a plus. Familiarity with Generative AI models and frameworks (e.g., GPT, DALL-E) Knowledge of machine learning frameworks (TensorFlow, PyTorch, Scikit-learn) will be a plus We back you with benefits that support your holistic well-being so you can be and deliver your best. This means caring for you and your loved ones' physical, financial, and mental health, as well as providing the flexibility you need to thrive personally and professionally: Competitive base salaries Bonus incentives Support for financial-well-being and retirement Comprehensive medical, dental, vision, life insurance, and disability benefits (depending on location) Flexible working model with hybrid, onsite or virtual arrangements depending on role and business need Generous paid parental leave policies (depending on your location) Free access to global on-site wellness centers staffed with nurses and doctors (depending on location) Free and confidential counseling support through our Healthy Minds program Career development and training opportunities American Express is an equal opportunity employer and makes employment decisions without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, veteran status, disability status, age, or any other status protected by law. Offer of employment with American Express is conditioned upon the successful completion of a background verification check, subject to applicable laws and regulations.

Senior Data Scientist (Deep Learning and Artificial Intelligence) Job Description We aim to bring about a new paradigm in medical image diagnostics; providing intelligent, holistic, ethical, explainable and patient centric care. We are looking for innovative problem solvers who love solving problems. We want people who can empathize with the consumer, understand business problems, and design and deliver intelligent products. People who are looking to extend artificial intelligence into unexplored areas. Your primary focus will be in applying deep learning and artificial intelligence techniques to the domain of medical image analysis. Responsibilities Selecting features, building and optimizing classifier engines using deep learning techniques. Understanding the problem and applying the suitable image processing techniques Use techniques from artificial intelligence/deep learning to solve supervised and unsupervised learning problems. Understanding and designing solutions for complex problems related to medical image analysis by using Deep Learning/Object Detection/Image Segmentation. Recommend and implement best practices around the application of statistical modeling. Create, train, test, and deploy various neural networks to solve complex problems. Develop and implement solutions to fit business problems which may include applying algorithms from a standard statistical tool, deep learning or custom algorithm development. Understanding the requirements and designing solutions and architecture in accordance with them is important. Participate in code reviews, sprint planning, and Agile ceremonies to drive high-quality deliverables. Design and implement scalable data science architectures for training, inference, and deployment pipelines. Ensure code quality, readability, and maintainability by enforcing software engineering best practices within the data science team. Optimize models for production, including quantization, pruning, and latency reduction for real-time inference. Drive the adoption of versioing strategies for models, datasets, and experiments (e.g., using MLFlow, DVC). Contribute to the architectural design of data platforms to support large-scale experimentation and production workloads. Skills and Qualifications Strong software engineering skills in Python (or other languages used in data science) with emphasis on clean code, modularity, and testability. Excellent understanding and hands-on of Deep Learning techniques such as ANN, CNN, RNN, LSTM, Transformers, VAEs etc. Must have experience with Tensorflow or PyTorch framework in building, training, testing, and deploying neural networks. Experience in solving problems in the domain of Computer Vision. Knowledge of data, data augmentation, data curation, and synthetic data generation. Ability to understand the complete problem and design the solutions that best fit all the constraints. Knowledge of the common data science and deep learning libraries and toolkits such as Keras, Pandas, Scikit-learn, Numpy, Scipy, OpenCV etc. Good applied statistical skills, such as distributions, statistical testing, regression, etc. Exposure to Agile/Scrum methodologies and collaborative development practices. Experience with the development of RESTful APIs. The knowledge of libraries like FastAPI and the ability to apply it to deep learning architectures is essential. Excellent analytical and problem-solving skills with a good attitude and keen to adapt to evolving technologies. Experience with medical image analysis will be an advantage. Experience designing and building ML architecture components (e.g., feature stores, model registries, inference servers). Solid understanding of software design patterns, microservices, and cloud-native architectures. Expertise in model optimization techniques (e.g., ONNX conversion, TensorRT, model distillation) Education : BE/B Tech MS/M Tech (will be a bonus) Experience : 3+ Years Job Type: Full-time Ability to commute/relocate: Gurugram, Haryana: Reliably commute or planning to relocate before starting work (Required) Application Question(s): Do you have experience leading teams in AI Development? Do you have experience creating software architecture for production environment in AI applications? Experience: Deep learning: 3 years (Required) Computer vision: 3 years (Required) PyTorch: 3 years (Required) Work Location: In person

Job Summary Gen AI Agentic AI Project Management Python Designing scalable GenAI systems (e.g. RAG pipelines multi-agent systems). Choosing between hosted APIs vs open-source models. Architecting hybrid systems (LLMs + traditional software). Model Evaluation & Selection Benchmarking models (e.g. GPT-4 Claude Mistral LLaMA). Responsibilities Strategic & Leadership-Level GenAI Skills AI Solution Architecture Designing scalable GenAI systems (e.g. RAG pipelines multi-agent systems). Choosing between hosted APIs vs open-source models. Architecting hybrid systems (LLMs + traditional software). Model Evaluation & Selection Benchmarking models (e.g. GPT-4 Claude Mistral LLaMA). Understanding trade-offs: latency cost accuracy context length. Using tools like LM Evaluation Harness OpenLLM Leaderboard etc. Enterprise-Grade RAG Systems Designing Retrieval-Augmented Generation pipelines. Using vector databases (Pinecone Weaviate Qdrant) with LangChain or LlamaIndex. Optimizing chunking embedding strategies and retrieval quality. Security Privacy & Governance Implementing data privacy access control and audit logging. Understanding risks: prompt injection data leakage model misuse. Aligning with frameworks like NIST AI RMF EU AI Act or ISO/IEC 42001. Cost Optimization & Monitoring Estimating and managing GenAI inference costs. Using observability tools (e.g. Arize WhyLabs PromptLayer). Token usage tracking and prompt optimization. Advanced Technical Skills Model Fine-Tuning & Distillation Fine-tuning open-source models using PEFT LoRA QLoRA. Knowledge distillation for smaller faster models. Using tools like Hugging Face Axolotl or DeepSpeed. Multi-Agent Systems Designing agent workflows (e.g. AutoGen CrewAI LangGraph). Task decomposition memory and tool orchestration. Toolformer & Function Calling Integrating LLMs with external tools APIs and databases. Designing tool-use schemas and managing tool routing. Team & Product Leadership GenAI Product Thinking Identifying use cases with high ROI. Balancing feasibility desirability and viability. Leading GenAI PoCs and MVPs. Mentoring & Upskilling Teams Training developers on prompt engineering LangChain etc. Establishing GenAI best practices and code reviews. Leading internal hackathons or innovation sprints.

Job Summary We’re seeking a hands-on GenAI & Computer Vision Engineer with 3–5 years of experience delivering production-grade AI solutions. You must be fluent in the core libraries, tools, and cloud services listed below, and able to own end-to-end model development—from research and fine-tuning through deployment, monitoring, and iteration. In this role, you’ll tackle domain-specific challenges like LLM hallucinations, vector search scalability, real-time inference constraints, and concept drift in vision models. Key Responsibilities Generative AI & LLM Engineering Fine-tune and evaluate LLMs (Hugging Face Transformers, Ollama, LLaMA) for specialized tasks Deploy high-throughput inference pipelines using vLLM or Triton Inference Server Design agent-based workflows with LangChain or LangGraph, integrating vector databases (Pinecone, Weaviate) for retrieval-augmented generation Build scalable inference APIs with FastAPI or Flask, managing batching, concurrency, and rate-limiting Computer Vision Development Develop and optimize CV models (YOLOv8, Mask R-CNN, ResNet, EfficientNet, ByteTrack) for detection, segmentation, classification, and tracking Implement real-time pipelines using NVIDIA DeepStream or OpenCV (cv2); optimize with TensorRT or ONNX Runtime for edge and cloud deployments Handle data challenges—augmentation, domain adaptation, semi-supervised learning—and mitigate model drift in production MLOps & Deployment Containerize models and services with Docker; orchestrate with Kubernetes (KServe) or AWS SageMaker Pipelines Implement CI/CD for model/version management (MLflow, DVC), automated testing, and performance monitoring (Prometheus + Grafana) Manage scalability and cost by leveraging cloud autoscaling on AWS (EC2/EKS), GCP (Vertex AI), or Azure ML (AKS) Cross-Functional Collaboration Define SLAs for latency, accuracy, and throughput alongside product and DevOps teams Evangelize best practices in prompt engineering, model governance, data privacy, and interpretability Mentor junior engineers on reproducible research, code reviews, and end-to-end AI delivery Required Qualifications You must be proficient in at least one tool from each category below: LLM Frameworks & Tooling: Hugging Face Transformers, Ollama, vLLM, or LLaMA Agent & Retrieval Tools: LangChain or LangGraph; RAG with Pinecone, Weaviate, or Milvus Inference Serving: Triton Inference Server; FastAPI or Flask Computer Vision Frameworks & Libraries: PyTorch or TensorFlow; OpenCV (cv2) or NVIDIA DeepStream Model Optimization: TensorRT; ONNX Runtime; Torch-TensorRT MLOps & Versioning: Docker and Kubernetes (KServe, SageMaker); MLflow or DVC Monitoring & Observability: Prometheus; Grafana Cloud Platforms: AWS (SageMaker, EC2/EKS) or GCP (Vertex AI, AI Platform) or Azure ML (AKS, ML Studio) Programming Languages: Python (required); C++ or Go (preferred) Additionally: Bachelor’s or Master’s in Computer Science, Electrical Engineering, AI/ML, or a related field 3–5 years of professional experience shipping both generative and vision-based AI models in production Strong problem-solving mindset; ability to debug issues like LLM drift, vector index staleness, and model degradation Excellent verbal and written communication skills Typical Domain Challenges You’ll Solve LLM Hallucination & Safety: Implement grounding, filtering, and classifier layers to reduce false or unsafe outputs Vector DB Scaling: Maintain low-latency, high-throughput similarity search as embeddings grow to millions Inference Latency: Balance batch sizing and concurrency to meet real-time SLAs on cloud and edge hardware Concept & Data Drift: Automate drift detection and retraining triggers in vision and language pipelines Multi-Modal Coordination: Seamlessly orchestrate data flow between vision models and LLM agents in complex workflows About Company Hi there! We are Auriga IT. We power businesses across the globe through digital experiences, data and insights. From the apps we design to the platforms we engineer, we're driven by an ambition to create world-class digital solutions and make an impact. Our team has been part of building the solutions for the likes of Zomato, Yes Bank, Tata Motors, Amazon, Snapdeal, Ola, Practo, Vodafone, Meesho, Volkswagen, Droom and many more. We are a group of people who just could not leave our college-life behind and the inception of Auriga was solely based on a desire to keep working together with friends and enjoying the extended college life. Who Has not Dreamt of Working with Friends for a Lifetime Come Join In https://www.aurigait.com/ -https://aurigait.com/https://aurigait.com

Company Description At StatusNeo, we are a global consulting firm specializing in AI, automation, and cloud-first digital solutions. We empower businesses with cutting-edge product & platform engineering to enhance user experience, design, and functionality. As advocates for digital transformation, we guide CXOs worldwide to embrace Digital, Data AI, and DevSecOps. Our exceptional work environment, recognized with the Great Place To Work certification, fosters innovation and collaboration. Role Description This is a full-time on-site role as a Solution Architect - Gen AI at StatusNeo located in Gurgaon. The Solution Architect will be responsible for designing and implementing innovative AI, automation, and cloud solutions. They will collaborate with clients to understand their needs, develop consulting strategies, lead software development projects, integrate solutions, and optimize business processes. Qualifications · Architect and deliver end-to-end GenAI platforms using AWS (ECS, RDS, Lambda, S3) with real-time LLM orchestration and RAG workflows. · Design and implement Python microservices with Redis caching and vector search using Qdrant or Redis Vector. · Integrate GenAI models and APIs (OpenAI, HuggingFace, LangChain,LangGraph), including containerized inference services and secured API pipelines. · Lead frontend architecture using Next.js (TypeScript) with SSR and scalable client-server routing. · Own infrastructure automation and DevOps using Terraform, AWS CDK, GitHub Actions, and Docker-based CI/CD pipelines. · Manage and optimize data architecture across Snowflake, PostgreSQL (RDS), and S3 for both analytical and transactional needs. · Knowledge of database pipeline and data quality, transitioning legacy systems to modular, cloud-native deployments. · Champion engineering culture, leading design/code reviews, mentoring team members, and aligning technical priorities with product strategy. · Ensure compliance, encryption, and data protection via AWS security best practices (IAM, Secrets Manager, WAF, API Gateway). --- Ideal Candidate Profile · Proven track record as a Solution Architect / Tech Lead on large-scale Data & AI products with GenAI integration. · Deep knowledge of AWS cloud services, microservices architecture, and full-stack deployment. · Strong understanding of ML lifecycle and productionization of LLMs / GenAI APIs. · Practical experience with design thinking, breaking down problems from user need to system delivery. · Excellent leadership, communication, and mentoring skills to drive team alignment and technical execution.

About us: Kantar is the world’s leading data, insights and consulting company. We understand more about how people think, feel, shop, share, vote and view than anyone else. Combining our expertise in human understanding with advanced technologies. Kantar’s 25,000 people based in more than 100 countries help the world’s leading organisations succeed and grow. Nobody knows people better than Kantar. We provide insight and inspiration to help our clients, our people and society to create and flourish in an extraordinary world. Our Worldpanel colleagues are the global experts in shopper behaviour, offering continuous monitoring, advanced analytics and tailored solutions to inspire successful decisions by leading organisations worldwide. Worldpanel turns purchase behaviour into a competitive advantage across a diverse range of markets including tech, fashion, telecoms and FMCG. Purpose of the role: A new role is being created by Kantar Worldpanel India team, who uses technology and analytical tools to link real purchase data with impactful and high- quality data which inspire successful decisions. We are looking for someone who aspires to the same growth as us and joins us in developing the Data Quality solution in a fast-changing market working alongside our commercial teams and internal research team to help our clients solve their business challenges. Playing a leading role in the delivery of strategic quality management is a critical part of the business to ensure consistent quality standards and methods, deliver strategic transformational projects and drive continuous improvement for the growth of the business and excellency of operations. This is a full-time, role based in Mumbai. WHAT'D YOU DO: (1) On a day-to-day basis, Act as custodian of project quality in all strategic and operational plans through experience and knowledge on consumer panel research operations. Accountable for tasks such as panel health & stability, sample designs, impact and pick up analysis factor creation etc. Maintain a strong, collaborative relationship with Client Service through data-driven decision making. (2) Quality Standards and Policies Implement and help define quality standards and policies, including KPI definitions for purchase quality management. Provide textual definitions and management standard information for Operations (OP) to implement. (3) Data Quality Assurance Act as the quality guardian for all consumer panel research Ensure good data quality before sending it to clients or uploading it to systems. Efficiently and timely investigate and resolve client data queries. Investigate problematic root causes and process flaws and provide solutions. (4) Panel Health and Sample Design Take responsibility for panel health, stability, sample design, and analysis factors. Own the sourcing and application of Universe data and its ongoing implementation. Provide annual Universe information and offer explanations for any changes. (5) Performance Monitoring and Auditing Audit local operational processes, define and monitor monthly results, and forecast to achieve panel and delivery targets. Regularly review and provide feedback on KPIs to OP teams. (6) Process and Improvement Maintain all procedures related to quality, including mechanisms for purchase management. Continuously identify areas for improvement and propose corrective actions. Monitor and review quality assurance. (7) Training and Education Educate Client Service (CS) and Operations teams on statistical data limitations according to sample sizes and sample design. Provide regular, high-quality local training content. (8) Collaboration and Communication Maintain strong collaborative relationships with customer service through data-driven decisions. Ensure all queries/issues are kept on track and solved on time, following local and regional processes. (9) Long run, you will.. Implement and help define quality standards and policy. Own the local audits of operating procedures, define & monitor monthly results, and forecast to achieve panel & delivery targets. Troubleshoot, resolve, remedy and overhaul where needed process defects which result in under-performance or non-delivery. Own and deliver local quality content training regularly. Productions of the above data matching, fraud detection, and data inference, by putting it into a technological environment Develop algorithm as well as statistical models to match and maximize the current data usage/automation. WHAT'D YOU BRING: Personal traits: stimulated by creative problem solving, comfortable with number, comfortable with ambiguity, work well autonomously but also happy to sit as part of a team, can focus on one specific task and not getting bored by the task, willing to learn and able to learn fast. Professional skills: excellent analytical skills; strong communication as you’ll need to explain the complex technical issues to people who might not have the data analysis or quality background; influencing the others in a rational way; creative thinking and solution-oriented; familiar with SPSS, Python or R, SQL , analytical innovation and automation ; computer coding skill is a plus but definitely a must-have. Minimum 2 tools knowledge is required. Academic background: Bachelor degree or above. Those who majored in Mathematics, Statistics and have certification in data quality might find quicker assimilation to the role but we do not intend to limit the range at all. Fluent in both English and Hindi. Work experience: Mini 8 years of work experience is preferred. If you have customized research experience before, or worked in a data analytics and research or statistics role, that would be a preferential advantage. Ability to communicate clearly and confidently, spoken and written, to levels of business locally and with Regional Quality team and peers in other markets. Ability to be self-motivated and independent as well as teamwork. Able to work under pressure to tight deadlines. With the following qualities… Inquisitive, with critical thinking, and demonstrate a genuine passion for consumer behaviour. Enjoys actively looking for new and more efficient ways of improving processes, raising standards, reducing errors, and overcoming omissions. Is proactive, optimistic, and willing to get involved to achieve the team's goals and objectives. Is highly collaborative and adaptable with the ability to work effectively within different cultural and technical environments. Possesses outstanding communication and interpersonal skills in order to comfortably connect with partners at all levels across the organization and facilitates discussions in a constructive manner. Join us! At Kantar, we want to create a more diverse community to expand our talent pool, be locally representative, drive diversity of thinking and better commercial outcomes. We also make sure we create an equality of opportunity in a fair and encouraging working environment where people feel included and accepted and are allowed to flourish in a space where their mental health and well-being are taken into consideration.

Senior Data Scientist (Deep Learning and Artificial Intelligence) Job Description We aim to bring about a new paradigm in medical image diagnostics; providing intelligent, holistic, ethical, explainable and patient centric care. We are looking for innovative problem solvers who love solving problems. We want people who can empathize with the consumer, understand business problems, and design and deliver intelligent products. People who are looking to extend artificial intelligence into unexplored areas. Your primary focus will be in applying deep learning and artificial intelligence techniques to the domain of medical image analysis. Responsibilities Selecting features, building and optimizing classifier engines using deep learning techniques. Understanding the problem and applying the suitable image processing techniques Use techniques from artificial intelligence/deep learning to solve supervised and unsupervised learning problems. Understanding and designing solutions for complex problems related to medical image analysis by using Deep Learning/Object Detection/Image Segmentation. Recommend and implement best practices around the application of statistical modeling. Create, train, test, and deploy various neural networks to solve complex problems. Develop and implement solutions to fit business problems which may include applying algorithms from a standard statistical tool, deep learning or custom algorithm development. Understanding the requirements and designing solutions and architecture in accordance with them is important. Participate in code reviews, sprint planning, and Agile ceremonies to drive high-quality deliverables. Design and implement scalable data science architectures for training, inference, and deployment pipelines. Ensure code quality, readability, and maintainability by enforcing software engineering best practices within the data science team. Optimize models for production, including quantization, pruning, and latency reduction for real-time inference. Drive the adoption of versioing strategies for models, datasets, and experiments (e.g., using MLFlow, DVC). Contribute to the architectural design of data platforms to support large-scale experimentation and production workloads. Skills and Qualifications Strong software engineering skills in Python (or other languages used in data science) with emphasis on clean code, modularity, and testability. Excellent understanding and hands-on of Deep Learning techniques such as ANN, CNN, RNN, LSTM, Transformers, VAEs etc. Must have experience with Tensorflow or PyTorch framework in building, training, testing, and deploying neural networks. Experience in solving problems in the domain of Computer Vision. Knowledge of data, data augmentation, data curation, and synthetic data generation. Ability to understand the complete problem and design the solutions that best fit all the constraints. Knowledge of the common data science and deep learning libraries and toolkits such as Keras, Pandas, Scikit-learn, Numpy, Scipy, OpenCV etc. Good applied statistical skills, such as distributions, statistical testing, regression, etc. Exposure to Agile/Scrum methodologies and collaborative development practices. Experience with the development of RESTful APIs. The knowledge of libraries like FastAPI and the ability to apply it to deep learning architectures is essential. Excellent analytical and problem-solving skills with a good attitude and keen to adapt to evolving technologies. Experience with medical image analysis will be an advantage. Experience designing and building ML architecture components (e.g., feature stores, model registries, inference servers). Solid understanding of software design patterns, microservices, and cloud-native architectures. Expertise in model optimization techniques (e.g., ONNX conversion, TensorRT, model distillation) Education : BE/B Tech MS/M Tech (will be a bonus) Experience : 3+ Years Job Type: Full-time Ability to commute/relocate: Gurugram, Haryana: Reliably commute or planning to relocate before starting work (Required) Application Question(s): Do you have experience leading teams in AI Development? Do you have experience creating software architecture for production environment in AI applications? Experience: Deep learning: 3 years (Required) Computer vision: 3 years (Required) PyTorch: 3 years (Required) Work Location: In person

About the Role: We are seeking an experienced MLOps Engineer to lead the deployment, scaling, and performance optimization of open-source Generative AI models on cloud infrastructure. You’ll work at the intersection of machine learning, DevOps, and cloud engineering to help productize and operationalize large-scale LLM and diffusion models. Key Responsibilities: Design and implement scalable deployment pipelines for open-source Gen AI models (LLMs, diffusion models, etc.). Fine-tune and optimize models using techniques like LoRA, quantization, distillation, etc. Manage inference workloads, latency optimization, and GPU utilization. Build CI/CD pipelines for model training, validation, and deployment. Integrate observability, logging, and alerting for model and infrastructure monitoring. Automate resource provisioning using Terraform, Helm, or similar tools on GCP/AWS/Azure. Ensure model versioning, reproducibility, and rollback using tools like MLflow, DVC, or Weights & Biases. Collaborate with data scientists, backend engineers, and DevOps teams to ensure smooth production rollouts. Required Skills & Qualifications: 5+ years of total experience in software engineering or cloud infrastructure. 3+ years in MLOps with direct experience in deploying large Gen AI models. Hands-on experience with open-source models (e.g., LLaMA, Mistral, Stable Diffusion, Falcon, etc.). Strong knowledge of Docker, Kubernetes, and cloud compute orchestration. Proficiency in Python and familiarity with model-serving frameworks (e.g., FastAPI, Triton Inference Server, Hugging Face Accelerate, vLLM). Experience with cloud platforms (GCP preferred, AWS or Azure acceptable). Familiarity with distributed training, checkpointing, and model parallelism. Good to Have: Experience with low-latency inference systems and token streaming architectures. Familiarity with cost optimization and scaling strategies for GPU-based workloads. Exposure to LLMOps tools (LangChain, BentoML, Ray Serve, etc.). Why Join Us: Opportunity to work on cutting-edge Gen AI applications across industries. Collaborative team with deep expertise in AI, cloud, and enterprise software. Flexible work environment with a focus on innovation and impact.

Hello, Truecaller is calling you from Bangalore, India! Ready to pick up? Our goal is to make communication smarter, safer, and more efficient, all while building trust everywhere. We're all about bringing you smart services with a big social impact, keeping you safe from fraud, harassment, scam calls or messages, so you can focus on the conversations that matter. Top 20 most downloaded apps globally, and world’s #1 caller ID and spam-blocking service for Android and iOS, with extensive AI capabilities, with more than 400 million active users per month. Founded in 2009, listed on Nasdaq OMX Stockholm and is categorized as a Large Cap. Our focus on innovation, operational excellence, sustainable growth, and collaboration has resulted in consistently high profitability and strong EBITDA margins. A team of 400 people from ~35 different nationalities spread across our headquarters in Stockholm and offices in Bangalore, Mumbai, Gurgaon and Tel Aviv with high ambitions. We in the Insights Team are responsible for SMS Categorization, Fraud detection and other Smart SMS features within the Truecaller app. The OTP & bank notifications, bill & travel reminder alerts are some examples of the Smart SMS features. The team has developed a patented offline text parser that powers all these features and the team is also exploring cutting edge technologies like LLM to enhance the Smart SMS features. The team’s mission is to become the World’s most loved and trusted SMS app which is aligned with Truecaller’s vision to make communication safe and efficient. Smart SMS is used by over 90M users every day. As an ML Engineer , you will be responsible for collecting, organizing, analyzing, and interpreting Truecaller data with a focus on NLP. In this role, you will be working hands-on to optimize the training and deployment of ML models to be quick and cost-efficient. Also, you will be pivotal in advancing our work with large language models and in-device models across diverse regions. Your expertise will enhance our natural language processing, machine learning, and predictive analytics capabilities. What you bring in : 3+ years in machine learning engineering, with hands-on involvement in feature engineering, model development, and deployment. Experience in Natural Language Processing (NLP), with a deep understanding of text processing, model development, and deployment challenges in the domain. Proven ability to develop, deploy, and maintain machine learning models in production environments, ensuring scalability, reliability, and performance. Strong familiarity with ML frameworks like TensorFlow, PyTorch, and ONNX, and experience in tech stack such as Kubernetes, Docker, APIs, Vertex AI, GCP. Experience deploying models across backend and mobile platforms. Fine-tune and optimize LLMs prompts for domain-specific applications Ability to optimize feature engineering, model training, and deployment strategies for performance and efficiency. Strong SQL and statistical skills. Programming knowledge in at least one language, such as Python or R. Preferably python. Knowledge of machine learning algorithms. Excellent teamwork and communication skills, with the ability to work cross-functionally with product, engineering, and data science teams. Good to have the knowledge in retrieval-based pipelines to enhance LLM performance The impact you will create: Collaborate with Product and Engineering to scope, design, and implement systems that solve complex business problems ensuring they are delivered on time and within scope. Design, develop, and deploy state-of-the-art NLP models, contributing directly to message classification and fraud detection at scale for millions of users. Leverage cutting-edge NLP techniques to enhance message understanding, spam filtering, and fraud detection, ensuring a safer and more efficient messaging experience. Build and optimize ML models that can efficiently handle large-scale data processing while maintaining accuracy and performance. Work closely with data scientists and data engineers to enable rapid experimentation, development, and productionization of models in a cost-effective manner. Streamline the ML lifecycle, from training to deployment, by implementing automated workflows, CI/CD pipelines, and monitoring tools for model health and performance. Stay ahead of advancements in ML and NLP, proactively identifying opportunities to enhance model performance, reduce latency, and improve user experience. Your work will directly impact millions of users, improving message classification, fraud detection, and the overall security of messaging platforms. It would be great if you also have: Understanding of Conversational AI Deploying NLP models in production Working knowledge of GCP components Cloud-based LLM inference with Ray, Kubernetes, and serverless architectures. Life at Truecaller - Behind the code: https://www.instagram.com/lifeattruecaller/ Sounds like your dream job? We will fill the position as soon as we find the right candidate, so please send your application as soon as possible. As part of the recruitment process, we will conduct a background check. This position is based in Bangalore , India. We only accept applications in English. What we offer: A smart, talented and agile team: An international team where ~35 nationalities are working together in several locations and time zones with a learning, sharing and fun environment. A great compensation package: Competitive salary, 30 days of paid vacation, flexible working hours, private health insurance, parental leave, telephone bill reimbursement, Udemy membership to keep learning and improving and Wellness allowance. Great tech tools: Pick the computer and phone that you fancy the most within our budget ranges. Office life: We strongly believe in the in-person collaboration and follow an office-first approach while offering some flexibility. Enjoy your days with great colleagues with loads of good stuff to learn from, daily lunch and breakfast and a wide range of healthy snacks and beverages. In addition, every now and then check out the playroom for a fun break or join our exciting parties and or team activities such as Lab days, sports meetups etc. There something for everyone! Come as you are: Truecaller is diverse, equal and inclusive. We need a wide variety of backgrounds, perspectives, beliefs and experiences in order to keep building our great products. No matter where you are based, which language you speak, your accent, race, religion, color, nationality, gender, sexual orientation, age, marital status, etc. All those things make you who you are, and that’s why we would love to meet you.

At American Express, our culture is built on a 175-year history of innovation, shared values and Leadership Behaviors, and an unwavering commitment to back our customers, communities, and colleagues. As part of Team Amex, you'll experience this powerful backing with comprehensive support for your holistic well-being and many opportunities to learn new skills, develop as a leader, and grow your career. Here, your voice and ideas matter, your work makes an impact, and together, you will help us define the future of American Express. How will you make an impact in this role? Enterprise Essentials team within Financial Data Engineering is hiring for a highly skilled Senior Engineering Manager with expertise in Python/Java Full Stack Development, Generative AI, Data Engineering, and Natural Language Processing. The Senior Engineering Manager will be working on creating new capabilities and modernizing existing ones in the domain of Global Tax, Finance and GSM Conversational AI platforms, and Enterprise essential products like Reconciliations, ERRM, Balancing and Control, Concur, and Ariba. The ideal candidate will be responsible for designing, developing, and maintaining scalable AI-driven applications and data pipelines. This role requires a deep understanding of NLP techniques, modern AI frameworks, data engineering best practices, and full-stack development to build innovative solutions that leverage machine learning and AI technologies. Key Responsibilities: Oversees and mentors a team of Software Engineering colleagues, enabling a culture of continuous learning, growth opportunities, and inclusivity for all individual colleagues and teams. Provides direct leadership and coaching to teams, supporting training and development of best practices. Manages resource allocation, project timeline, and budget for Software Engineering projects, ensuring alignment with organizational goals. Collaborates with senior leadership to hire top talent for the team, ensuring a high-functioning and cohesive unit, implementing strategies for talent retention and professional development Leads the development, deployment, support, and monitoring of software across various environments. Collaborates with senior leadership and cross-functional teams to define and implement technology roadmaps and strategies. Leads teams to innovate and automate processes, driving efficiency and scalability in production environments. Drives continuous improvement initiatives, leveraging metrics and feedback to improve team performance and software quality. Collaborates and co-creates effectively with teams in product and the business to align technology initiatives with business objectives. Full Stack Development: Design and develop scalable and secure applications using Java / Python framework, and front-end technologies such as React. Implement and optimize microservices, APIs, and server-side logic for AI-based platforms. Develop and maintain cloud-based, containerized applications (Docker, Kubernetes). Design, optimize, and deploy high-performance systems ensuring minimal latency and maximum throughput. Architect solutions for real-time processing, ensuring low-latency data retrieval and high system availability. Troubleshoot and enhance system performance, optimizing for large-scale, real-time, distributed and COTS applications. Generative AI & Machine Learning: Develop, and deploy innovative solutions in Tax, and finance using ML & Generative AI models leveraging frameworks such as langchain. Implement NLP algorithms for language understanding, text summarization, information extraction, and conversational agents. Create pipelines for training and deploying AI models efficiently in production environments. Collaborate with data scientists to optimize and scale AI/NLP solutions. Integrate AI/ML models into applications, ensuring proper scaling, optimization, and monitoring of models in production. Design solutions that enable fast and efficient inference for real-time AI applications. Data Engineering: Build and maintain data pipelines to support AI/ML model development and deployment. Design and develop ETL processes to ingest, clean, and process large-scale structured and unstructured datasets. Work with data storage and retrieval solutions like SQL/NoSQL databases, data lakes, and cloud storage (GCP, AWS, or Azure). Ensure data integrity, security, and performance of the data pipelines. Collaboration & Leadership: Lead cross-functional teams to deliver high-quality, AI-driven products. Lead and mentor engineers and collaborate with product managers, data scientists, and business stakeholders to ensure alignment with project goals. Keep up-to-date with the latest advancements in AI, NLP, and data engineering, and provide technical guidance to the team. Takes accountability for the success of the team achieving their goals Drives the team’s strategy and prioritizes initiatives Influence team members by challenging status quo, demonstrating risk taking, and implementing creative ideas. Be a productivity multiplier for your team by analysing your workflow and contributing to enable the team to be more effective, productive, and demonstrating faster and stronger results. Mentor and guide team members to success within the team Minimum Qualifications Education: Bachelor’s or Master’s in Computer Science, Engineering, Data Science, or a related field. 10+ years of experience in software engineering in architecture and design (architecture, design patterns, reliability and scaling) of new and existing systems. Strong experience in developing full stack software in Java or Python, data engineering, and AI/NLP solutions and demonstrated ability to quickly learn new languages. Following standard Engineering excellence standards while building software. Leveraging code assistants like Github Copilot. Writing great prompts for generating high quality code, tests, and other artefacts like documentation. Proficiency in data engineering tools and frameworks like GCP BigQuery, Apache Spark, Kafka. Proficiency with containerization (Docker, Kubernetes), CI/CD pipelines, and version control. Experience with RESTful API design, microservices architecture, and cloud platforms (AWS / GCP / Azure). Preferred Qualifications Experience working with large-scale AI systems in production environments. Familiarity with modern AI research and developments in Generative AI and NLP. `Strong understanding of DevOps and Infrastructure-as-Code (Terraform, Ansible). Proven track record of delivering AI-driven products that scale Understanding of MLOps practices will be a plus. Familiarity with Generative AI models and frameworks (e.g., GPT, DALL-E) Knowledge of machine learning frameworks (TensorFlow, PyTorch, Scikit-learn) will be a plus We back you with benefits that support your holistic well-being so you can be and deliver your best. This means caring for you and your loved ones' physical, financial, and mental health, as well as providing the flexibility you need to thrive personally and professionally: Competitive base salaries Bonus incentives Support for financial-well-being and retirement Comprehensive medical, dental, vision, life insurance, and disability benefits (depending on location) Flexible working model with hybrid, onsite or virtual arrangements depending on role and business need Generous paid parental leave policies (depending on your location) Free access to global on-site wellness centers staffed with nurses and doctors (depending on location) Free and confidential counseling support through our Healthy Minds program Career development and training opportunities American Express is an equal opportunity employer and makes employment decisions without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, veteran status, disability status, age, or any other status protected by law. Offer of employment with American Express is conditioned upon the successful completion of a background verification check, subject to applicable laws and regulations.

Job Role: AI Engineer (WFO - Chennai) Experience: 3years Job Type: Full Time, Permanent Job Location: Chennai (5days - work from office) Notice Period: Immediate to 15days We are looking for a passionate AI Engineer with 1–3 years of hands-on experience in developing and deploying AI/ML models. You will contribute to designing scalable AI systems, training models, and supporting real-world deployment for autonomous vehicles and other AI-centric applications. If you're enthusiastic about applying your AI skills in impactful projects, join our innovative team. Roles & Responsibilities: Build and optimize AI/ML models for real-time autonomous driving systems. Work closely with senior architects and product teams to translate business problems into AI solutions. Implement and test deep learning models (e.g., CNNs, transformers) for tasks such as object detection, lane recognition, or natural language understanding. Integrate AI models into production environments and contribute to continuous model improvement. Collaborate with MLOps teams to ensure reliable deployment through CI/CD pipelines. Write clean, well-documented, and efficient code. Stay up-to-date with the latest research and best practices in AI and Machine Learning. Requirements: Required Technical and Professional Expertis e 1–3 years of experience in AI/ML development and deployment. Proficiency in Python and common ML frameworks (TensorFlow, PyTorch). Experience with data preprocessing, model training, evaluation, and optimization. Solid foundation in machine learning and deep learning algorithms. Experience working with APIs, model versioning, and deployment workflows. Familiarity with computer vision, NLP, or reinforcement learning. Hands-on experience with Docker, Git, and cloud services (AWS, GCP, or Azure). Strong problem-solving and analytical skills. Good communication skills and ability to work in a collaborative environment. Preferred Skills: Experience with real-time inference and edge deployment. Familiarity with autonomous systems or robotics applications. Exposure to LLMs (e.g., GPT, BERT) or multimodal AI models. Experience with RESTful APIs, microservices, and distributed systems. Educational Qualifications: Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Machine Learning, or a related field. Benefits Innovative Projects: Work on cutting-edge AI technologies shaping the future of mobility. Collaborative Culture: Join a passionate team pushing boundaries in AI and autonomy. Career Growth: Be part of a fast-growing startup with plenty of growth opportunities. Benefits: Competitive salary, health insurance (up to ₹20 lakhs), wellness programs, learning & development, mentorship, and performance-based increments.

InCommon is hiring on behalf of an early-stage digital commerce startup. Location: HSR Layout, Bangalore (In-office only) Experience: 6 - 10 years About the Role: We’re looking for a Senior Product Manager to lead our Catalog Infrastructure & Distribution Platform. This is a foundational layer that powers product data across all touchpoints - D2C sites, marketplaces, offline retail, and more. You’ll build systems to collect, enrich, template, and distribute catalog content at scale - turning fragmented, unstructured product data into consistent, API-ready, multi-channel feeds. This role sits at the intersection of data modeling, workflow automation, API integration, and UI tooling - with high visibility across engineering, design, and GTM. Responsibilities: Define the vision for a single source of truth for catalog data across the ShopOS stack Build tools to collect and enrich unstructured item data from various brand systems Create smart templates for product attributes (code, design, specs, etc.) Design and manage the catalog creation-to-distribution flow with click-to-publish functionality Integrate with external APIs (e.g. marketplaces, ERP systems, offline retail PoS) for automated sync Drive automation for SKU setup, versioning, updates, and distribution rules Own the productization of catalog intelligence (attribute inference, bulk edits, Gen AI enrichments) Requirements: 6–10 years of product management experience in eCommerce, supply chain, or SaaS platforms Strong understanding of catalog management, PIM/DAM systems, or ERP integration Experience working on data-heavy platforms or backend-heavy workflows Ability to work with engineering on data pipelines, versioning logic, and API schemas Sharp execution and MVP mindset - can break down complexity into simple workflows Comfort working with brands and ops teams to understand real-world catalog challenges Good to have: Background in Gen AI or automation tooling Experience with retailer onboarding, SKU mapping, and marketplace API integrations Prior work on catalog enrichment (images, specs, variants, sizing, etc.) Why This Role Matters: Your work will power the foundational layer of commerce at ShopOS - enabling our AI agents to act on consistent, clean product data. This system will touch every brand we support and directly impact how fast and intelligently they go to market. Our Values: Extreme ownership and bias for action Honest, high-velocity communication Respect for craft and obsession with users Fast, scrappy iteration over perfection Low ego, high empathy, radical candor What We Offer: Competitive salary Health & wellness benefits Work from our vibrant HSR Layout (Bangalore) or Chennai (Nungambakkam) office Direct mentorship from AI & commerce leaders Zero-bureaucracy, high-ownership environment Opportunity to shape the future of agentic commerce at internet scale

Location: Bangalore - Karnataka, India - EOIZ Industrial Area Job Family: Engineering Worker Type Reference: Regular - Permanent Pay Rate Type: Salary Career Level: T3(B) Job ID: R-44637-2025 Description & Requirements Job Description Introduction: A Career at HARMAN Digital Transformation Solutions (DTS) We’re a global, multi-disciplinary team that’s putting the innovative power of technology to work and transforming tomorrow. At HARMAN DTS, you solve challenges by creating innovative solutions. Combine the physical and digital, making technology a more dynamic force to solve challenges and serve humanity’s needs Java Microservices Java Developer with experience in microservices deployment, automation, and system lifecycle management(security, and infrastructure management) Required Skills: Java, hibernate, SAML/OpenSAML REST APIs Docker PostgreSQL (PSQL) Familiar with git hub workflow. Good to Have: Go (for automation and bootstrapping) RAFT Consensus Algorithm HashiCorp Vault Key Responsibilities: Service Configuration & Automation: Configure and bootstrap services using the Go CLI. Develop and maintain Go workflow templates for automating Java-based microservices. Deployment & Upgrade Management: Manage service upgrade workflows and apply Docker-based patches. Implement and manage OS-level patches as part of the system lifecycle. Enable controlled deployments and rollbacks to minimize downtime. Network & Security Configuration: Configure and update FQDN, proxy settings, and SSL/TLS certificates. Set up and manage syslog servers for logging and monitoring. Manage appliance users, including root and SSH users, ensuring security compliance. Scalability & Performance Optimization: Implement scale-up and scale-down mechanisms for resource optimization. Ensure high availability and performance through efficient resource management. Lifecycle & Workflow Automation: Develop automated workflows to support service deployment, patching, and rollback. Ensure end-to-end lifecycle management of services and infrastructure. What You Will Do To perform in-depth analysis of data and machine learning models to identify insights and areas of improvement. Develop and implement models using both classical machine learning techniques and modern deep learning approaches. Deploy machine learning models into production, ensuring robust MLOps practices including CI/CD pipelines, model monitoring, and drift detection. Conduct fine-tuning and integrate Large Language Models (LLMs) to meet specific business or product requirements. Optimize models for performance and latency, including the implementation of caching strategies where appropriate. Collaborate cross-functionally with data scientists, engineers, and product teams to deliver end-to-end ML solutions. What You Need to Be Successful Utilized various statistical techniques to derive important insights and trends. Proven experience in machine learning model development and analysis using classical and neural networks based approaches. Strong understanding of LLM architecture, usage, and fine-tuning techniques. Solid understanding of statistics, data preprocessing, and feature engineering. Proficient in Python and popular ML libraries (scikit-learn, PyTorch, TensorFlow, etc.). Strong debugging and optimization skills for both training and inference pipelines. Familiarity with data formats and processing tools (Pandas, Spark, Dask). Experience working with transformer-based models (e.g., BERT, GPT) and Hugging Face ecosystem. Bonus Points if You Have Experience with MLOps tools (e.g., MLflow, Kubeflow, SageMaker, or similar). Experience with monitoring tools (Prometheus, Grafana, or custom solutions for ML metrics). Familiarity with cloud platforms (Sagemaker, AWS, GCP, Azure) and containerization (Docker, Kubernetes). Hands-on experience with MLOps practices and tools for deployment, monitoring, and drift detection. Exposure to distributed training and model parallelism techniques. Prior experience in AB testing ML models in production. What Makes You Eligible Bachelor’s or master’s degree in computer science, Artificial Intelligence, or a related field. 5-10 years relevant and Proven experience in developing and deploying generative AI models and agents in a professional setting. What We Offer Flexible work environment, allowing for full-time remote work globally for positions that can be performed outside a HARMAN or customer location Access to employee discounts on world-class Harman and Samsung products (JBL, HARMAN Kardon, AKG, etc.) Extensive training opportunities through our own HARMAN University Competitive wellness benefits Tuition reimbursement “Be Brilliant” employee recognition and rewards program An inclusive and diverse work environment that fosters and encourages professional and personal development You Belong Here HARMAN is committed to making every employee feel welcomed, valued, and empowered. No matter what role you play, we encourage you to share your ideas, voice your distinct perspective, and bring your whole self with you – all within a support-minded culture that celebrates what makes each of us unique. We also recognize that learning is a lifelong pursuit and want you to flourish. We proudly offer added opportunities for training, development, and continuing education, further empowering you to live the career you want. About HARMAN: Where Innovation Unleashes Next-Level Technology Ever since the 1920s, we’ve been amplifying the sense of sound. Today, that legacy endures, with integrated technology platforms that make the world smarter, safer, and more connected. Across automotive, lifestyle, and digital transformation solutions, we create innovative technologies that turn ordinary moments into extraordinary experiences. Our renowned automotive and lifestyle solutions can be found everywhere, from the music we play in our cars and homes to venues that feature today’s most sought-after performers, while our digital transformation solutions serve humanity by addressing the world’s ever-evolving needs and demands. Marketing our award-winning portfolio under 16 iconic brands, such as JBL, Mark Levinson, and Revel, we set ourselves apart by exceeding the highest engineering and design standards for our customers, our partners and each other. If you’re ready to innovate and do work that makes a lasting impact, join our talent community today ! HARMAN is an Equal Opportunity/Affirmative Action employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, or Protected Veterans status. HARMAN offers a great work environment, challeng Important Notice: Recruitment Scams Please be aware that HARMAN recruiters will always communicate with you from an '@harman.com' email address. We will never ask for payments, banking, credit card, personal financial information or access to your LinkedIn/email account during the screening, interview, or recruitment process. If you are asked for such information or receive communication from an email address not ending in '@harman.com' about a job with HARMAN, please cease communication immediately and report the incident to us through: harmancareers@harman.com. HARMAN is proud to be an Equal Opportunity / Affirmative Action employer. All qualified applicants will receive consideration for employment without regard to race, religion, color, national origin, gender (including pregnancy, childbirth, or related medical conditions), sexual orientation, gender identity, gender expression, age, status as a protected veteran, status as an individual with a disability, or other applicable legally protected characteristics.

Our Company Changing the world through digital experiences is what Adobe’s all about. We give everyone—from emerging artists to global brands—everything they need to design and deliver exceptional digital experiences! We’re passionate about empowering people to create beautiful and powerful images, videos, and apps, and transform how companies interact with customers across every screen. We’re on a mission to hire the very best and are committed to creating exceptional employee experiences where everyone is respected and has access to equal opportunity. We realize that new ideas can come from everywhere in the organization, and we know the next big idea could be yours! The Opportunity The Identity and Administration team is looking for a motivated and versatile data analyst to drive Data & Insights for business decision making and growth testing. You will employ data to deeply understand customers through their administrative journey. The ideal candidate will have deep technical skills, a passion for delivering compelling customer analytics, curiosity, comfort with ambiguity, and able to influence partners to drive strategy. What you'll Do Lead strategic analytics projects, presenting findings that provide impactful insights for key collaborators. Apply data from various sources to understand customer behavior, including in-product engagement, purchase patterns, and retention. Build compelling narratives to drive action and find opportunities to improve the administration experiences. Develop agile Analysis frameworks to ensure quick and high-quality data insights that advise strategic decisions. Collaborate closely with Product teams to successfully implement the right strategies for Identity-based experiences in fast paced, data-driven environment. Design, implement, and analyze A/B experiments, delivering comprehensive reports and actionable insights to drive product improvements. Partner with enablement and development teams to ensure accurate analytics measurement across existing and new features, supporting data systems. Build and maintain dashboards to facilitate self-serve information access for teams. What you need to succeed A Bachelor's degree or equivalent experience in computer science, statistics, physics, or a related field. Technical experience of a similar level will also be taken into account. 5-7+ years of direct experience as a Data Analyst. Deep understanding of statistics and expertise in building, productizing, maintaining, and improving predictive models is preferred. Strong proficiency in querying, manipulating, validating, and analyzing large datasets using SQL or Hive. Experience in ML modeling and data inference is highly desirable. Proficiency with Python, R, or any other scripting language. Experience with data visualization tools such as Tableau or Power BI. Familiarity with Adobe Analytics and Amplitude is a plus. Strong self-starter with a proven track record of delivering business insights that have crafted product strategy. Outstanding communication and teamwork skills to work effectively with multidisciplinary teams. Adobe is proud to be an Equal Employment Opportunity employer. We do not discriminate based on gender, race or color, ethnicity or national origin, age, disability, religion, sexual orientation, gender identity or expression, veteran status, or any other applicable characteristics protected by law. Learn more about our vision here. Adobe aims to make Adobe.com accessible to any and all users. If you have a disability or special need that requires accommodation to navigate our website or complete the application process, email accommodations@adobe.com or call (408) 536-3015.

We're not your average tech company! Rightcrowd is a global leader in keeping people safe and organizations secure. We build smart solutions that manage who's on-site, what access they have, and ensure everything is compliant. Think big names – Fortune 50 and ASX 10 companies rely on us to tackle their toughest security challenges. We're a passionate, global team with offices in places like Australia, the USA, Belgium, India, and the Philippines, and we're on a mission to make the world a safer place, one clever line of code at a time. What We Offer Competitive salary and benefits. A collaborative, respectful, and high-accountability team culture. Opportunities for growth within a global finance team. Flexibility in a remote-friendly and dynamic work environment. Key Responsibilities Required Qualifications & Skills: Agentic AI Development & Code Generation: Design, implement, and lead the development of an advanced agentic AI system that can interpret user stories and autonomously generate production-ready code Research and implement state-of-the-art techniques in LLM prompting, fine-tuning, and orchestration to achieve optimal code generation results Architect robust evaluation systems to test, validate, and improve AI-generated code Seamlessly integrate AI-generated code into existing CI/CD pipelines Collaborate with product and engineering teams to refine inputs and ensure alignment with development standards AI Recommendation Engine Architecture: Architect a high-performance, scalable recommendation engine for the RightCrowd SmartAccess platform Design and implement AI-driven feature extraction pipelines Develop hybrid recommendation algorithms leveraging both collaborative filtering and content- based approaches Engineer systems for real-time inference and continuous model improvement Ensure the architecture integrates seamlessly with existing product infrastructure Natural Language Reporting System Development: Lead the end-to-end development of an AI-powered reporting system that translates natural language queries to SQL Engineer robust NLP components to accurately understand and parse user requests Build a reliable translation layer between natural language and database queries Implement data retrieval, processing, and presentation mechanisms Design systems for generating insights and visualizations from retrieved data Ensure appropriate data security and access controls Technical Leadership & Innovation: Provide architectural guidance across AI initiatives within the organization Design scalable, maintainable AI systems with consideration for cloud infrastructure and MLOps best practices Stay at the forefront of advancements in LLMs, agentic AI, and code generation technologies Mentor junior engineers and foster a culture of AI innovation Collaborate effectively with cross-functional teams Master's or Ph.D. in Computer Science, AI, or related field (or equivalent practical experience) 5+ years of experience building production-level AI systems with significant focus on LLMs and generative AI Demonstrated expertise in Python and modern AI frameworks (PyTorch, TensorFlow, Hugging Face Transformers) Extensive experience with LLM orchestration frameworks (LangChain, LangGraph, or similar) Proven track record designing and implementing agentic AI systems Strong proficiency in prompt engineering, fine-tuning, and optimization of LLMs Expert-level SQL skills and experience with database systems Experience with cloud platforms (AWS, Azure, GCP) and their AI/ML services Solid understanding of software engineering principles and best practices Experience with MLOps and CI/CD pipelines for AI systems Preferred Qualifications: Experience developing systems that generate production-ready code Familiarity with retrieval-augmented generation (RAG) techniques Experience with vector databases (Pinecone, Weaviate, etc.) Knowledge of containerization technologies (Docker, Kubernetes) Experience with model optimization, quantization, and efficient inference Contributions to open-source AI projects or research publications Familiarity with physical security or identity access management domains Experience implementing AI systems with strong security and governance controls This position offers the opportunity to work at the forefront of AI engineering, developing systems that not only generate code but also function autonomously to deliver real business R&D Ghaziabad, India

About Clarifai Clarifai is a leading, compute orchestration AI platform specializing in computer vision and generative AI. We empower organizations to transform unstructured image, video, text, and audio data into actionable insights, significantly faster and more accurately than manual processes. Founded in 2013 by Matt Zeiler, Ph.D., Clarifai has been at the forefront of AI innovation since achieving the top five placements in the 2013 ImageNet Challenge. Our diverse, globally distributed team operates across the United States, Canada, Estonia, Argentina, and India. We have secured $100M in funding, including a $60M Series C round, backed by industry leaders such as Menlo Ventures, Union Square Ventures, Lux Capital, NEA, LDV Capital, Corazon Capital, Google Ventures, NVIDIA, Qualcomm, and Osage. Clarifai is proud to be an equal-opportunity workplace committed to building and maintaining a diverse and inclusive team. The Opportunity As a Senior Research Scientist at Clarifai, you'll contribute to applied research initiatives, converting the latest academic insights into production-ready solutions. You'll collaborate closely with our MLOps, Engineering, Business Development, and Product teams to rapidly prototype and deliver innovative capabilities, particularly within the national security domain. Your deep expertise in Computer Vision, GenAI, and multi-modal AI will drive strategic advancements and customer success. We seek individuals passionate about impactful AI applications, committed to collaboration, and skilled in managing multi-phase projects from initial proof-of-concept through deployment. Continuous learning and active participation in academic and industry forums are core elements of our research environment. Key Responsibilities Train, evaluate, and optimize machine learning models for high performance, scalability, and robustness. Contribute to R&D in object detection and multi-object tracking for remote sensing, including Synthetic Aperture Radar (SAR), and rapidly prototype proof-of-concept systems. Leverage and build AI data engines—scalable feedback systems that integrate model inference, human-guided labeling, and automated evaluation—to accelerate dataset growth and model refinement. Design and deliver production-grade, maintainable code while managing multi-phase development aligned to technical and customer objectives. Collaborate across teams and stakeholders—especially in national security and defense—to ensure effective knowledge transfer and mission-aligned innovation. Impact Your work as a Senior Research Scientist will significantly influence Clarifai's capability to deliver innovative AI solutions to the national security and intelligence communities. You will directly contribute to strategic projects that enhance Clarifai's reputation and position as a market leader in AI-driven geospatial analysis. Requirements 3+ years of hands-on experience developing neural networks, focusing particularly on Computer Vision and/or GenAI. Expertise in Python, with strong proficiency in libraries such as PyTorch, TensorFlow, or Jax. Advanced degree (Master's or PhD) in Computer Science, Mathematics, Engineering, or related fields. Great to Have Experience working with government, defense, or intelligence community R&D projects. Familiarity with remote sensing data sources, including commercial satellite imagery, UAS video, and NTM. Experience with LLMs, RAG, PEFT, and multi-modal applications (e.g., Captioning, VQA, cross-modal retrieval). Familiarity with the Model Context Protocol (MCP) and its use in structured agent communication, task orchestration, and context management across multi-agent systems. Published research in Computer Vision, NLP, or multi-modal AI. PhD in Machine Learning or related disciplines.

Job Description 💰 Compensation Note: The budget for this role is fixed at INR 50–55 lakhs per annum (non-negotiable). Please ensure this aligns with your expectations before applying. 📍 Work Setup: This is a hybrid role , requiring 3 days per week onsite at the office in Hyderabad, India . 📝 Interview Process: The process consists of 6 stages , including a technical assessment, code review, code discussion , and panel interviews . Company Description: Blend is a premier AI services provider, committed to co-creating meaningful impact for its clients through the power of data science, AI, technology, and people. With a mission to fuel bold visions, Blend tackles significant challenges by seamlessly aligning human expertise with artificial intelligence. The company is dedicated to unlocking value and fostering innovation for its clients by harnessing world-class people and data-driven strategy. We believe that the power of people and AI can have a meaningful impact on your world, creating more fulfilling work and projects for our people and clients. Job Description : We are looking for an AI Engineer with experience in Speech-to-text and Text Generation to solve a Conversational AI challenge for our client based in EMEA. The focus of this project is to transcribe conversations and leverage generative AI-powered text analytics to drive better engagement strategies and decision-making. The ideal candidate will have deep expertise in Speech-to-Text (STT), Natural Language Processing (NLP), Large Language Models (LLMs), and Conversational AI systems. This role involves working on real-time transcription, intent analysis, sentiment analysis, summarization, and decision-support tools. Key Responsibilities: Conversational AI & Call Transcription Development Develop and fine-tune automatic speech recognition (ASR) models Implement language model fine-tuning for industry-specific language. Develop speaker diarization techniques to distinguish speakers in multi-speaker conversations. NLP & Generative AI Applications Build summarization models to extract key insights from conversations. Implement Named Entity Recognition (NER) to identify key topics. Apply LLMs for conversation analytics and context-aware recommendations. Design custom RAG (Retrieval-Augmented Generation) pipelines to enrich call summaries with external knowledge. Sentiment Analysis & Decision Support Develop sentiment and intent classification models. Create predictive models that suggest next-best actions based on call content, engagement levels, and historical data. AI Deployment & Scalability Deploy AI models using tools like AWS, GCP, Azure AI, ensuring scalability and real-time processing. Optimize inference pipelines using ONNX, TensorRT, or Triton for cost-effective model serving. Implement MLOps workflows to continuously improve model performance with new call data. Qualifications: Technical Skills Strong experience in Speech-to-Text (ASR), NLP, and Conversational AI. Hands-on expertise with tools like Whisper, DeepSpeech, Kaldi, AWS Transcribe, Google Speech-to-Text. Proficiency in Python, PyTorch, TensorFlow, Hugging Face Transformers. Experience with LLM fine-tuning, RAG-based architectures, and LangChain. Hands-on experience with Vector Databases (FAISS, Pinecone, Weaviate, ChromaDB) for knowledge retrieval. Experience deploying AI models using Docker, Kubernetes, FastAPI, Flask. Soft Skills Ability to translate AI insights into business impact. Strong problem-solving skills and ability to work in a fast-paced AI-first environment. Excellent communication skills to collaborate with cross-functional teams, including data scientists, engineers, and client stakeholders. Preferred Qualifications Experience in healthcare, pharma, or life sciences NLP use cases. Background in knowledge graphs, prompt engineering, and multimodal AI. Experience with Reinforcement Learning (RLHF) for improving conversation models.

Job Description Job Title: Senior Python Developer – AI Architecture Location: Onsite in Pune (NIBM (Kondhwa) Pune Experience: 4+ Years Job Type: Full-Time Shift: 11 AM - 8 PM IST) Skills: Flask, FastAPI, or Django, AI/ML frameworks (e.g., TensorFlow, PyTorch, scikit-learn) Joining: Immediate (This is a backfill role, so we need someone who can join in a week) About The Role We are seeking a seasoned Python Developer to join our AI Engineering team. You will play a key role in designing and implementing scalable, AI-driven systems and microservices that power intelligent applications across our platform. Key Responsibilities Design and develop robust, scalable backend systems using Python. Collaborate with ML/AI engineers to integrate AI/ML models into production. Architect and implement APIs and microservices for AI workflows. Optimize the performance of data pipelines and inference engines. Ensure code quality through unit testing, code reviews, and CI/CD practices. Work with cloud platforms (AWS/GCP/Azure) to deploy and monitor AI/MS services Requirements Required Skills: startup culture fit and mindset Strong problem-solving skills Strong proficiency in Python (Flask, FastAPI, or Django). Solid understanding of software architecture and design patterns. Experience with AI/ML frameworks (e.g., TensorFlow, PyTorch, scikit-learn). Familiarity with containerization (Docker, Kubernetes). Hands-on experience with RESTful APIs and asynchronous programming. Exposure to data engineering tools (Airflow, Spark, Kafka) is a plus. Preferred Qualifications Bachelor’s or Master’s in Computer Science, Engineering, or a related field. Experience working in agile teams and DevOps environments. Knowledge of MLOps practices and model lifecycle man.

Role : Applied AI Engineer (Gen-AI, Vision) Function : Applied AI Compensation : 40-60 LPA + ESOPs About the Company: A venture-backed, stealth-stage technology company building next-gen matchmaking and relationship platforms is hiring their founding AI/ML & Data Engineering Team. They are on a mission to reimagine how people connect, using AI, community, and content as the building blocks. They’re not building just another dating app — they’re creating an experience where users feel: “This app gets me.” At the core of the product are real-time, ML recommendation engines — similar to Spotify for song moods or TikTok for discovery. They are well funded and backed by marquee VCs in India and US. Company Philosophy: Core belief: Great data + Good models = Great recommendations Good data + Great models = Average recommendations That’s why they’re investing in data infrastructure from the inception and foundation. Position Overview: As an Applied AI Engineer, you'll lead the deployment of advanced vision-language models to power a personalised, photorealistic user experience. Your work will focus on fine-tuning and integrating models like Stable Diffusion, LoRA, and CLIP into real-time pipelines, optimising them for user delight, performance, accuracy, and eventually costs. You will collaborate closely with product and design teams to bring generative AI capabilities to deliver a novel dating experience. Role & Responsibilities: Build and deploy cutting-edge vision-language pipelines (e.g., Stable Diffusion, LoRA, CLIP, BLIP) for personalised and authentic user profile visuals Fine-tune LoRA models to reflect a user's best version while maintaining identity integrity Design scalable APIs for image generation, editing, and personalization Work with UX/design to integrate image-generation flows that feel intuitive and delightful Optimize models for mobile performance, fast inference, and cost efficiency Collaborate closely with product, backend, and ML researchers to productionize ideas Ideal Profile: They are looking for a hands-on applied AI/ML engineer with expertise in generative vision models like Stable Diffusion, and some track record of building real-time, personalised generative AI experiences. Experience with computer vision, generative models, or deep learning Experience working with Stable Diffusion, LoRA training, and prompt engineering Exposure to different vision-language architectures like Flux, CLIP, BLIP etc Proficient in PyTorch or equivalent ML frameworks Strong understanding of image pipelines, dataset curation, and captioning Experience deploying ML models on cloud-based services ( at minimum Replicate, Hugging Face Spaces and preferably on GPUs) Comfortable writing production-ready Python, working with versioned models and real-time inference stacks Passionate about building beautiful, human-centred AI experiences Nice to have: Prior experience with personalization, avatars, or face-preserving generative models Contributed to open-source vision models or fine-tuning libraries Experience in a startup or fast-paced product-focused team What the role offers: Join a founding team where your work is core to product experience Shape the future of how humans connect in the AI era Significant ESOPs and wealth creation + competitive cash compensation

About the Role: We are looking for a forward-thinking LLMOps Engineer to join our team and help build the next generation of secure, scalable, and responsible Generative AI (GenAI) platforms. This role will focus on establishing governance, security, and operational best practices while enabling development teams to build high-performing GenAI applications. You will also work closely with GenAI agents and integrate LLMs from multiple providers to support diverse use cases. Key Responsibilities: Design and implement governance frameworks for GenAI platforms, ensuring compliance with internal policies and external regulations (e.g., GDPR, AI Act). Define and enforce responsible AI practices including fairness, transparency, explainability, and auditability. Implement robust security protocols including IAM, data encryption, secure API access, and model sandboxing. Collaborate with security teams to conduct risk assessments and ensure secure deployment of LLMs. Build and maintain scalable LLMOps pipelines for model training, fine-tuning, evaluation, deployment, and monitoring. Automate model lifecycle management with CI/CD, versioning, rollback, and observability. Develop and manage GenAI agents capable of reasoning, planning, and tool use. Integrate and orchestrate LLMs from multiple providers (e.g., OpenAI, Anthropic, Cohere, Google, Azure OpenAI) to support hybrid and fallback strategies. Optimize prompt engineering, context management, and agent memory for production use. Ensure high availability, low latency, and cost-efficiency of GenAI workloads across cloud and hybrid environments. Implement monitoring and alerting for model drift, hallucinations, and performance degradation. Partner with GenAI developers to embed best practices and reusable components (SDKs, templates, APIs). Provide technical guidance and documentation to accelerate development and ensure platform consistency. Qualifications: Bachelor’s or Master’s degree in Computer Science, Engineering, or related field. 4+ years of experience in MLOps, DevOps, or platform engineering, with 1–2 years in LLM/GenAI environments. Deep understanding of LLMs, GenAI agents, prompt engineering, and inference optimization. Experience with LangChain, LlamaIndex, Langraph or similar agent frameworks. Hands-on with MLflow, or equivalent tools. Proficient in Python, containerization (Docker) and cloud platforms (AWS/GCP/Azure). Familiarity with AI governance frameworks and responsible AI principles. Experience with vector databases (e.g., FAISS, Pinecone), RAG pipelines, and model evaluation frameworks. Knowledge of Responsible AI, red-teaming, and OWASP security priciples.

Years of exp :10 - 15 yrs Location : Noida Join us as Cloud Engineer Lead at Dailoqa , where you will be responsible for operationalizing cutting-edge machine learning and generative AI solutions, ensuring scalable, secure, and efficient deployment across infrastructure. You will work closely with data scientists, ML engineers, and business stakeholders to build and maintain robust MLOps pipelines, enabling rapid experimentation and reliable production implementation of AI models, including LLMs and real-time analytics systems. To be successful as Cloud Engineer you should have experience with: Cloud sourcing, networks, VMs, performance, scaling, availability, storage, security, access management Deep expertise in one or more cloud platforms: AWS, Azure, GCP Strong experience in containerization and orchestration (Docker, Kubernetes, Helm) Familiarity with CI/CD tools: GitHub Actions, Jenkins, Azure DevOps, ArgoCD, etc. Proficiency in scripting languages (Python, Bash, PowerShell) Knowledge of MLOps tools such as MLflow, Kubeflow, SageMaker, Vertex AI, or Azure ML Strong understanding of DevOps principles applied to ML workflows. Key Responsibilities may include: Design and implement scalable, cost-optimized, and secure infrastructure for AI-driven platforms. Implement infrastructure as code using tools like Terraform, ARM, or Cloud Formation. Automate infrastructure provisioning, CI/CD pipelines, and model deployment workflows. Ensure version control, repeatability, and compliance across all infrastructure components. Set up monitoring, logging, and alerting frameworks using tools like Prometheus, Grafana, ELK, or Azure Monitor. Optimize performance and resource utilization of AI workloads including GPU-based training/inference Experience with Snowflake, Databricks for collaborative ML development and scalable data processing. Understanding model interpretability, responsible AI, and governance. Contributions to open-source MLOps tools or communities. Strong leadership, communication, and cross-functional collaboration skills. Knowledge of data privacy, model governance, and regulatory compliance in AI systems. Exposure to LangChain, Vector DBs (e. g. , FAISS, Pinecone), and retrieval-augmented generation (RAG) pipelines.