1209 Inference Jobs

About Us Yubi stands for ubiquitous. But Yubi will also stand for transparency, collaboration, and the power of possibility. From being a disruptor in India’s debt market to marching towards global corporate markets from one product to one holistic product suite with seven products Yubi is the place to unleash potential. Freedom, not fear. Avenues, not roadblocks. Opportunity, not obstacles. About Yubi Yubi, formerly known as CredAvenue, is re-defining global debt markets by freeing the flow of finance between borrowers, lenders, and investors. We are the world's possibility platform for the discovery, investment, fulfillment, and collection of any debt solution. At Yubi, opportunities are plenty and we equip you with tools to seize it. In March 2022, we became India's fastest fintech and most impactful startup to join the unicorn club with a Series B fundraising round of $137 million. In 2020, we began our journey with a vision of transforming and deepening the global institutional debt market through technology. Our two-sided debt marketplace helps institutional and HNI investors find the widest network of corporate borrowers and debt products on one side and helps corporates to discover investors and access debt capital efficiently on the other side. Switching between platforms is easy, which means investors can lend, invest and trade bonds - all in one place. All of our platforms shake up the traditional debt ecosystem and offer new ways of digital finance. Yubi Credit Marketplace - With the largest selection of lenders on one platform, our credit marketplace helps enterprises partner with lenders of their choice for any and all capital requirements. Yubi Invest - Fixed income securities platform for wealth managers & financial advisors to channel client investments in fixed income Financial Services Platform - Designed for financial institutions to manage co-lending partnerships & asset based securitization Spocto - Debt recovery & risk mitigation platform Corpository - Dedicated SaaS solutions platform powered by Decision-grade data, Analytics, Pattern Identifications, Early Warning Signals and Predictions to Lenders, Investors and Business Enterprises So far, we have on-boarded over 17000+ enterprises, 6200+ investors & lenders and have facilitated debt volumes of over INR 1,40,000 crore. Backed by marquee investors like Insight Partners, B Capital Group, Dragoneer, Sequoia Capital, LightSpeed and Lightrock, we are the only-of-its-kind debt platform globally, revolutionizing the segment. At Yubi, People are at the core of the business and our most valuable assets. Yubi is constantly growing, with 1000+ like-minded individuals today, who are changing the way people perceive debt. We are a fun bunch who are highly motivated and driven to create a purposeful impact. Come, join the club to be a part of our epic growth story. Responsibilities This particular role is within our Yubi Invest vertical, and you would get to work on building our bonds platform, called Aspero, for retail users. Be able to operate in ambiguous situations and define clear objectives by breaking down the narratives independently. Work closely with business, research, data and engineering teams to understand the user goals, market dynamics and ship products. Aligning product strategy, proposition and roadmap with measurable metrics with all stakeholders. Drive PRDs, product planning, and product design of new features and enhancements. Clearly communicate product and platform benefits to our users and internal stakeholders About The Role- We’re looking for a highly skilled, results-driven AI engineer who thrives in fast-paced, high-impact environments. If you are passionate about pushing the boundaries of Computer Vision, OCR, and Large Language Models (LLMs) and have a strong foundation in building and deploying AI solutions, this role is for you. As a Senior Data Scientist, you will take ownership of designing and implementing state-of-the-art OCR and Computer Vision systems. This role demands deep technical expertise, the ability to work autonomously, and a mindset that embraces complex challenges head-on. Here, you won’t just fine-tune pre-trained models—you’ll be architecting, optimizing, and scaling AI solutions that power real-world applications. Key Responsibilities- Architect, develop, and deploy high-performance Computer Vision and OCR models for real-world applications. Implement and optimize state-of-the-art OCR models such as Donut, TrOCR, LayoutLM, and DocFormer for document processing and information extraction. Fine-tune and integrate LLMs (GPT, LLaMA, Mistral, etc.) to enhance text understanding and automation. Develop custom deep learning models for large-scale image and document processing. Build and optimize end-to-end AI pipelines, ensuring efficient data processing and model deployment. Work closely with engineers to operationalize AI models in production (Docker, FastAPI, TensorRT, ONNX). Enhance GPU performance and model inference efficiency, applying techniques such as quantization and pruning. Stay ahead of industry advancements, continuously experimenting with new AI architectures and training techniques. Work in a highly dynamic, startup-like environment, balancing rapid experimentation with production-grade robustness. Requirements 5-10 years experience p roven technical expertise – Strong programming skills in Python, PyTorch, TensorFlow with deep experience in Computer Vision and OCR. Hands-on experience in developing, training, and deploying OCR and document AI models. Deep understanding of Transformer-based architectures for vision and text processing. Experience working with Hugging Face, OpenCV, TensorRT, and NVIDIA GPUs for model acceleration. Autonomous problem solver – You take initiative, work independently, and drive projects from research to production. Strong experience in scaling AI solutions, including model optimization and deployment on cloud platforms (AWS/GCP/Azure). Thrives in fast-paced environments – You embrace challenges, pivot quickly, and execute effectively. Familiarity with MLOps tools (Docker, FastAPI, Kubernetes) for seamless model deployment. Experience in multi-modal models (Vision + Text). Nice to Have- Strong background in vector databases, RAG pipelines, and fine-tuning LLMs for document intelligence. Contributions to open-source AI projects.

Company: Qualcomm India Private Limited Job Area: Engineering Group, Engineering Group > Software Engineering General Summary: More details below: Join the exciting Generative AI team at Qualcomm focused on integrating cutting edge GenAI models on Qualcomm chipsets. The team uses Qualcomm chips’ extensive heterogeneous computing capabilities to allow inference of GenAI models on-device without a need for connection to the cloud. Our inference engine is designed to help developers run neural network models trained in a variety of frameworks on Snapdragon platforms at blazing speeds while still sipping the smallest amount of power. Utilize this power efficient hardware and Software stack to run Large Language Models (LLMs) and Large Vision Models (LVM) at near GPU speeds! Responsibilities: In this role, you will spearhead the development and commercialization of the Qualcomm AI Runtime (QAIRT) SDK on Qualcomm SoCs. As an AI inferencing expert, you'll push the limits of performance from large models. Your mastery in deploying large C/C++ software stacks using best practices will be essential. You'll stay on the cutting edge of GenAI advancements, understanding LLMs/Transformers and the nuances of edge-based GenAI deployment. Most importantly, your passion for the role of edge in AI's evolution will be your driving force. Requirements: Master’s/Bachelor’s degree in computer science or equivalent. 4+ years of relevant work experience in software development. Strong understanding of Generative AI models – LLM, LVM and LLMs and building blocks Floating-point, Fixed-point representations and Quantization concepts. Experience with optimizing algorithms for AI hardware accelerators (like CPU/GPU/NPU). Strong development skills in C/C++ Excellent analytical and debugging skills. Good communication skills (verbal, presentation, written). Ability to collaborate across a globally diverse team and multiple interests. Preferred Qualifications Strong understanding of SIMD processor architecture and system design. Proficiency in object-oriented software development. Familiarity with Linux and Windows environment Strong background in kernel development for SIMD architectures. Familiarity with frameworks like llama.cpp, MLX, and MLC is a plus. Good knowledge of PyTorch, TFLite, and ONNX Runtime is preferred. Experience with parallel computing systems and Assembly is a plus. Minimum Qualifications: Bachelor's degree in Engineering, Information Systems, Computer Science, or related field and 2+ years of Software Engineering or related work experience. OR Master's degree in Engineering, Information Systems, Computer Science, or related field and 1+ year of Software Engineering or related work experience. OR PhD in Engineering, Information Systems, Computer Science, or related field. 2+ years of academic or work experience with Programming Language such as C, C++, Java, Python, etc. Applicants : Qualcomm is an equal opportunity employer. If you are an individual with a disability and need an accommodation during the application/hiring process, rest assured that Qualcomm is committed to providing an accessible process. You may e-mail disability-accomodations@qualcomm.com or call Qualcomm's toll-free number found here. Upon request, Qualcomm will provide reasonable accommodations to support individuals with disabilities to be able participate in the hiring process. Qualcomm is also committed to making our workplace accessible for individuals with disabilities. (Keep in mind that this email address is used to provide reasonable accommodations for individuals with disabilities. We will not respond here to requests for updates on applications or resume inquiries). Qualcomm expects its employees to abide by all applicable policies and procedures, including but not limited to security and other requirements regarding protection of Company confidential information and other confidential and/or proprietary information, to the extent those requirements are permissible under applicable law. To all Staffing and Recruiting Agencies : Our Careers Site is only for individuals seeking a job at Qualcomm. Staffing and recruiting agencies and individuals being represented by an agency are not authorized to use this site or to submit profiles, applications or resumes, and any such submissions will be considered unsolicited. Qualcomm does not accept unsolicited resumes or applications from agencies. Please do not forward resumes to our jobs alias, Qualcomm employees or any other company location. Qualcomm is not responsible for any fees related to unsolicited resumes/applications. If you would like more information about this role, please contact Qualcomm Careers.

Position Overview BayOne Solutions is seeking an exceptional AI/ML Engineer to join our innovative technology initiatives that will revolutionize talent acquisition through intelligent automation. This role is critical to developing and implementing cutting-edge AI/ML solutions that will transform core business processes and drive operational excellence. As our AI/ML Engineer, you will architect and deploy sophisticated machine learning models, implement generative AI solutions, and build multimodal AI systems that transform how we connect talent with opportunities. This position offers the opportunity to work with Fortune 500 clients while building scalable AI solutions that will define the future of our technology platform. Key Responsibilities AI/ML Model Development & Implementation (40%) Design and implement advanced machine learning algorithms for candidate-job matching, utilizing semantic understanding and behavioral prediction models Develop natural language processing solutions for job description parsing, candidate profile analysis, and automated content generation Build and optimize recommendation engines that intelligently match candidates to opportunities based on skills, experience, and cultural fit Create predictive models for recruitment outcomes, including candidate success probability and time-to-fill optimization Implement anomaly detection systems for candidate screening and quality assurance Generative AI & Large Language Models (25%) Develop and fine-tune large language models (LLMs) for recruitment-specific applications including automated job description generation, candidate communication, and interview preparation materials Implement RAG (Retrieval-Augmented Generation) systems for intelligent document processing and candidate information extraction Build conversational AI systems for candidate pre-screening, interview scheduling, and engagement campaigns Create prompt engineering solutions and implement advanced generative AI workflows using GPT, LLaMA, and other foundation models Develop multimodal AI applications that process text, voice, and structured data for comprehensive candidate assessment Data Pipeline & Integration (20%) Design and implement robust data pipelines for processing candidate profiles, job descriptions, and recruitment metrics Build ETL processes for integrating multiple data sources including internal systems, critical platforms, and external APIs Develop real-time data processing systems for candidate sourcing and matching operations Implement data quality monitoring and validation systems ensuring high-quality inputs for ML models Create scalable data architectures supporting AI model training, inference, and continuous learning Platform Integration & Deployment (15%) Integrate AI/ML models with the Django-based Recruitment 2.0 platform through RESTfuI APIs and microservices architecture Deploy models to production environments using containerization (Docker) and cloud platforms (Azure/AWS) Implement A/B testing frameworks for model performance evaluation and continuous improvement Build monitoring and alerting systems for model performance, drift detection, and system health Collaborate with full-stack developers to ensure seamless integration of AI capabilities into user- facing applications Required Qualifications Education & Experience Bachelor's degree in Computer Science, Data Science, Machine Learning, or related technical field 2+ years of hands-on experience in machine learning, deep learning, and AI model development Proven track record developing and deploying AI/ML solutions in production environments Experience working with enterprise clients and understanding business requirements for AI applications Technical Skills Programming Languages: Expert-level Python proficiency; experience with C++, SQL, and web technologies ML/AI Frameworks: Advanced experience with TensorFlow, PyTorch, Keras, scikit-learn, and Huggin Face Transformers Generative AI & LLMs: Hands-on experience with GPT models, fine-tuning techniques, prompt engineering, and foundation models NLP & Text Processing: Strong background in natural language processing, text classification, named entity recognition, and semantic analysis Data Processing: Proficiency with NumPy, Pandas, and large-scale data processing frameworks Cloud & DevOps: Experience with Azure/AWS, Docker, Git, and CI/CD pipelines for ML model deployment Databases: Working knowledge of SQL databases, NoSQL systems, and vector databases for AI applications Specialized Experience Experience with multimodal AI systems processing text, audio, and structured data Background in recommendation systems, matching algorithms, and information retrieval Knowledge of automated assessment systems and candidate evaluation methodologies Experience with real-time AI applications and low-latency model serving Understanding of bias detection and fairness in AI systems, particularly for human-oriented applications Preferred Qualifications Master's degree in Machine Learning, AI, or related field Background in developing Al-powered applications for complex business processes Knowledge of federated learning and distributed AI system architectures Experience with document processing, OCR, and information extraction systems Familiarity with enterprise software integration patterns and API development Application Process We are looking for candidates who can start immediately and contribute to our fast-paced, innovative environment. Please submit your resume along with examples of AI/ML projects you've developed, particularly those involving NLP, generative AI, or recommendation systems. Equal Opportunity Employer: Bayone Solutions is committed to creating a diverse and inclusive workplace and is proud to be an equal opportunity employer. This position o[fers an exceptional opportunity to shape the[uture of recruitment technology while working with cutting-edge AI systems and enterprise clients. Join us in building the next generation o[talent solutions.

Software Engineer – AI/ML/LLM/Data Science Company Overview: Entra Solutions (A BSI Financial Services company) is a FinTech company specialized in technology based financial solutions and services for the mortgage Industry. We are a people-focused, growth-oriented, innovative company and we're looking for people like you to make a positive change and join our team today! We are looking for an innovative Software Engineer – AI/ML/LLM/Data Science to design, develop, and deploy AI-driven solutions using Machine Learning, NLP, and Large Language Models (LLMs). The ideal candidate will work with Python to build and optimize retrieval-augmented generation (RAG) systems, LLM fine-tuning, and vector search technologies. You will develop scalable AI pipelines, ensuring high performance and seamless integration with cloud and on-prem environments. This role involves MLOps best practices, AI model optimization, and deployment of intelligent applications. WHAT YOU WILL DO: Develop, fine-tune, and deploy AI/ML models and LLM-based applications for real-world use cases. Build and optimize retrieval-augmented generation (RAG) systems using Vector Databases (e.g., ChromaDB, Pinecone, FAISS). Work on LLM fine-tuning, embeddings, and prompt engineering to enhance model performance. Develop end-to-end AI solutions with APIs using FastAPI, Flask, or similar frameworks. Build and maintain scalable data pipelines for training and inferencing AI models. Deploy and manage models using MLOps best practices on AWS or Azure. Optimize AI model performance for low-latency inference and scalability. Collaborate with cross-functional teams (Product, Engineering, Data Science) to integrate AI capabilities into applications. WHAT WE’RE LOOKING FOR: Must Have: Proficiency in Python – Strong hands-on experience in AI/ML frameworks like TensorFlow, PyTorch, Hugging Face, LangChain, OpenAI APIs. Good to Have: Experience with LLM fine-tuning, embeddings, and transformers. Knowledge of NLP, vector search technologies (ChromaDB, Pinecone, FAISS, Milvus). Experience in building scalable AI models and data pipelines with Spark, Kafka, or Dask. Familiarity with MLOps tools (Docker, Kubernetes, CI/CD for AI models). Hands-on experience in cloud-based AI deployment (AWS Lambda, SageMaker, GCP Vertex AI, Azure ML). Knowledge of prompt engineering, GPT models, or knowledge graphs. WHAT’S IN IT FOR YOU? Competitive Salary & Full Benefits Package PTOs / Medical Insurance Exposure to cutting-edge AI/LLM projects in an innovative environment Career Growth Opportunities in AI/ML leadership Collaborative & AI-driven work culture EEO Statement We are an equal employment opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, gender, national origin, disability status, protected veteran status or any other characteristic protected by law.

Machine Learning Engineer (L1) Experience Required: 2-4 years As a Machine Learning Engineer at Spring, you’ll help bring data-driven intelligence into our products and operations. You’ll support the development and deployment of models and pipelines that power smarter decisions, more personalized experiences, and scalable automation. This is an opportunity to build hands-on experience in real-world ML and AI systems while collaborating with experienced engineers and data scientists. You’ll work on data processing, model training, and integration tasks — gaining exposure to the entire ML lifecycle, from experimentation to production deployment. You’ll learn how to balance model performance with system requirements, and how to structure your code for reliability, observability, and maintainability. You’ll use modern ML/AI tools such as scikit-learn, HuggingFace, and LLM APIs — and be encouraged to explore AI techniques that improve our workflows or unlock new product value. You’ll also be expected to help build and support automated data pipelines, inference services, and validation tools as part of your contributions. You’ll work closely with engineering, product, and business stakeholders to understand how models drive value. Over time, you’ll build the skills and judgment needed to identify impactful use cases, communicate technical trade-offs, and contribute to the broader evolution of ML at Spring. What You’ll Do Support model development and deployment across structured and unstructured data and AI use cases. Build and maintain automated pipelines for data processing, training, and inference. Use ML and AI tools (e.g., scikit-learn, LLM APIs) in day-to-day development. Collaborate with engineers, data scientists, and product teams to scope and deliver features. Participate in code reviews, testing, and monitoring practices. Integrate ML systems into customer-facing applications and internal tools. Identify differences in data distribution that could affect model performance in real-world applications. Stay up to date with developments in the machine learning industry. Tech Expectations Core Skills Curiosity, attention to detail, strong debugging skills, and eagerness to learn through feedback Solid foundation in statistics and data interpretation Strong understanding of data structures, algorithms, and software development best practices Exposure to data pipelines, model training and evaluation, or training workflows Languages Must Have: Python, SQL ML Algorithms Must Have: Traditional modeling techniques (e.g., tree models, Naive Bayes, logistic regression) Ensemble methods (e.g., XGBoost, Random Forest, CatBoost, LightGBM) ML Libraries / Frameworks Must Have: scikit-learn, Hugging Face, Statsmodels, Optuna Good to Have: SHAP, Pytest Data Processing / Manipulation Must Have: pandas, NumPy Data Visualization Must Have: Plotly, Matplotlib Version Control Must Have: Git Others – Good to Have AWS (e.g., EC2, SageMaker, Lambda) Docker Airflow MLflow Github Actions

Job Family Data Science & Analysis (India) Travel Required Up to 25% Clearance Required None What You Will Do Design, train, and fine-tune advanced foundational models (text, audio, vision) using healthcare-and other relevant datasets, focusing on accuracy and context relevance. Collaborate with cross-functional teams (Business, engineering, IT) to seamlessly integrate AI/ML technologies into our solution offerings. Deploy, monitor, and manage AI models in a production environment, ensuring high availability, scalability, and performance. Continuously research and evaluate the latest advancements in AI/ML and industry trends to drive innovation. Ensure all AI solutions adhere to industry standards and regulatory requirements (i.e., HIPAA). Develop and maintain comprehensive documentation for AI models, including development, training, fine-tuning, and deployment procedures. Provide technical guidance and mentorship to junior AI engineers and team members. Collaborate with stakeholders to understand business needs and translate them into technical requirements for model fine-tuning and development. Select and curate appropriate datasets for fine-tuning foundational models to address specific use cases. Implement robust security protocols to protect sensitive data from breaches and unauthorized access. Ensure AI solutions can seamlessly integrate with existing systems and applications. What You Will Need Bachelors or master’s in computer science, Artificial Intelligence, Machine Learning, or a related field. 10+ year industry experience with minimum of 5 years of hands-on experience in AI/ML, with a demonstrable track record of training and deploying LLMs and other machine learning models. Strong proficiency in Python and familiarity with popular AI/ML frameworks (TensorFlow, PyTorch, Hugging Face Transformers, etc.). Practical experience deploying and managing AI models in production environments, including expertise in serving and inference frameworks (Triton, TensorRT, VLLM, TGI, etc.). Experience in Voice AI applications, a solid understanding of healthcare data standards (FHIR, HL7, EDI) and regulatory compliance (HIPAA, SOC2) is preferred. Excellent problem-solving and analytical abilities, capable of tackling complex challenges and evaluating multiple factors. Exceptional communication and collaboration skills, enabling effective teamwork in a dynamic environment. Experience with cloud computing platforms (AWS, Azure) and containerization technologies (Docker, Kubernetes) is a plus. Familiarity with MLOps practices for continuous integration, continuous deployment (CI/CD), and automated monitoring of AI models. Delivered a minimum of 3 to 5 AI/LLM medium to large scale projects of significant value. What We Offer What Would Be Nice to Have: Guidehouse offers a comprehensive, total rewards package that includes competitive compensation and a flexible benefits package that reflects our commitment to creating a diverse and supportive workplace. About Guidehouse Guidehouse is an Equal Opportunity Employer–Protected Veterans, Individuals with Disabilities or any other basis protected by law, ordinance, or regulation. Guidehouse will consider for employment qualified applicants with criminal histories in a manner consistent with the requirements of applicable law or ordinance including the Fair Chance Ordinance of Los Angeles and San Francisco. If you have visited our website for information about employment opportunities, or to apply for a position, and you require an accommodation, please contact Guidehouse Recruiting at 1-571-633-1711 or via email at RecruitingAccommodation@guidehouse.com. All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodation. All communication regarding recruitment for a Guidehouse position will be sent from Guidehouse email domains including @guidehouse.com or guidehouse@myworkday.com. Correspondence received by an applicant from any other domain should be considered unauthorized and will not be honored by Guidehouse. Note that Guidehouse will never charge a fee or require a money transfer at any stage of the recruitment process and does not collect fees from educational institutions for participation in a recruitment event. Never provide your banking information to a third party purporting to need that information to proceed in the hiring process. If any person or organization demands money related to a job opportunity with Guidehouse, please report the matter to Guidehouse’s Ethics Hotline. If you want to check the validity of correspondence you have received, please contact recruiting@guidehouse.com. Guidehouse is not responsible for losses incurred (monetary or otherwise) from an applicant’s dealings with unauthorized third parties. Guidehouse does not accept unsolicited resumes through or from search firms or staffing agencies. All unsolicited resumes will be considered the property of Guidehouse and Guidehouse will not be obligated to pay a placement fee.

Experience : 2.00 + years Salary : INR 1500000-2500000 / year (based on experience) Expected Notice Period : 30 Days Shift : (GMT+05:30) Asia/Kolkata (IST) Opportunity Type : Office (Pune) Placement Type : Full Time Permanent position(Payroll and Compliance to be managed by: Anervea.AI) (*Note: This is a requirement for one of Uplers' client - Anervea.AI) What do you need for this opportunity? Must have skills required: Airflow, LLMs, NLP, Statistical Modeling, Predictive Analysis, Forecasting, Python, SQL, MLFlow, pandas, Scikit-learn, XgBoost Anervea.AI is Looking for: As an ML / Data Science Engineer at Anervea, you’ll work on designing, training, deploying, and maintaining machine learning models across multiple products. You’ll build models that predict clinical trial outcomes, extract insights from structured and unstructured healthcare data, and support real-time scoring for sales or market access use cases. You’ll collaborate closely with AI engineers, backend developers, and product owners to translate data into product features that are explainable, reliable, and impactful. Key Responsibilities Develop and optimize predictive models using algorithms such as XGBoost, Random Forest, Logistic Regression, and ensemble methods Engineer features from real-world healthcare data (clinical trials, treatment adoption, medical events, digital behavior) Analyze datasets from sources like ClinicalTrials.gov, PubMed, Komodo, Apollo.io, and internal survey pipelines Build end-to-end ML pipelines for inference and batch scoring Collaborate with AI engineers to integrate LLM-generated features with traditional models Ensure explainability and robustness of models using SHAP, LIME, or custom logic Validate models against real-world outcomes and client feedback Prepare clean, structured datasets using SQL and Pandas Communicate insights clearly to product, business, and domain teams Document all processes, assumptions, and model outputs thoroughly Technical Skills Required : Strong programming skills in Python (NumPy, Pandas, scikit-learn, XGBoost, LightGBM) Experience with statistical modeling and classification algorithms Solid understanding of feature engineering, model evaluation, and validation techniques Exposure to real-world healthcare, trial, or patient data (strong bonus) Comfortable working with unstructured data and data cleaning techniques Knowledge of SQL and NoSQL databases Familiarity with ML lifecycle tools (MLflow, Airflow, or similar) Bonus: experience working alongside LLMs or incorporating generative features into ML Bonus: knowledge of NLP preprocessing, embeddings, or vector similarity methods Personal Attributes : Strong analytical and problem-solving mindset Ability to convert abstract questions into measurable models Attention to detail and high standards for model quality Willingness to learn life sciences concepts relevant to each use case Clear communicator who can simplify complexity for product and business teams Independent learner who actively follows new trends in ML and data science Reliable, accountable, and driven by outcomes—not just code Bonus Qualities : Experience building models for healthcare, pharma, or biotech Published work or open-source contributions in data science Strong business intuition on how to turn models into product decisions How to apply for this opportunity? Step 1: Click On Apply! And Register or Login on our portal. Step 2: Complete the Screening Form & Upload updated Resume Step 3: Increase your chances to get shortlisted & meet the client for the Interview! About Uplers: Our goal is to make hiring reliable, simple, and fast. Our role will be to help all our talents find and apply for relevant contractual onsite opportunities and progress in their career. We will support any grievances or challenges you may face during the engagement. (Note: There are many more opportunities apart from this on the portal. Depending on the assessments you clear, you can apply for them as well). So, if you are ready for a new challenge, a great work environment, and an opportunity to take your career to the next level, don't hesitate to apply today. We are waiting for you!

Key Responsibility Lead the fine-tuning and domain adaptation of open-source LLMs (e.g., LLaMA 3) using frameworks like vLLM, HuggingFace, DeepSpeed, and PEFT techniques. Develop data pipelines to ingest, clean, and structure cybersecurity data, including threat intelligence reports, CVEs, exploits, malware analysis, and configuration files. Collaborate with cybersecurity analysts to build taxonomy and structured knowledge representations to embed into LLMs. Drive the design and execution of evaluation frameworks specific to cybersecurity tasks (e.g., classification, summarization, anomaly detection). Own the lifecycle of model development including training, inference optimization, testing, and deployment. Provide technical leadership and mentorship to a team of ML engineers and researchers. Stay current with advances in LLM architectures, cybersecurity datasets, and AI-based threat detection. Advocate for ethical AI use and model robustness, especially given the sensitive nature of cybersecurity data Requirements Required Skills: 5+ years of experience in machine learning, with at least 2 years focused on LLM training or fine-tuning. Strong experience with vLLM, HuggingFace Transformers, LoRA/QLoRA, and distributed training techniques. Proven experience working with cybersecurity data—ideally including MITRE ATT&CK, CVE/NVD databases, YARA rules, Snort/Suricata rules, STIX/TAXII, or malware datasets. Proficiency in Python, ML libraries (PyTorch, Transformers), and MLOps practices. Familiarity with prompt engineering, RAG (Retrieval-Augmented Generation), and vector stores like FAISS or Weaviate. Demonstrated ability to lead projects and collaborate across interdisciplinary teams. Excellent problem-solving skills and strong written & verbal communication. Nice to Have Experience deploying models via vLLM in production environments with FastAPI or similar APIs. Knowledge of cloud-based ML training (AWS/GCP/Azure) and GPU infrastructure. Background in reverse engineering, malware analysis, red teaming, or threat hunting. Publications, open-source contributions, or technical blogs in the intersection of AI and cybersecurity.

Visa is a world leader in payments and technology, with over 259 billion payments transactions flowing safely between consumers, merchants, financial institutions, and government entities in more than 200 countries and territories each year. Our mission is to connect the world through the most innovative, convenient, reliable, and secure payments network, enabling individuals, businesses, and economies to thrive while driven by a common purpose – to uplift everyone, everywhere by being the best way to pay and be paid. Make an impact with a purpose-driven industry leader. Join us today and experience Life at Visa. Job Description Visa's Cybersecurity team provides enterprise-wide, risk-based cybersecurity policies, practices, and solutions to protect Visa’s systems and data from internal and external threats. To protect Visa’s assets in this dynamic threat landscape, they are deploying new cyber-security tools, collaborating across industries, and taking a proactive approach to monitoring the cyberspace beyond the Visa network. As part of Cyber Threat Analytics and Research team (CTAR) , you will leverage cutting-edge technologies to perform statistical profiling, inference, classification, clustering and predictive analysis. As a key member of the technical team, you will create and implement sophisticated machine learning models to help derive new insights to defend against cyber-attacks. You will be working with a large variety of data sets, cutting-edge security technologies, and world-class operation teams to create awesome analytics for security and other business units. Essential Functions: Analyze cyber event logs using Spark and big data technologies and develop deeper insights into products using advanced statistical methods. Formulate cyber threat scenarios into technical data problems and develop high fidelity models to capture unseen threats Devise and implement deep learning models for building user behavior profiles. This includes data acquisition, feature engineering, model development, and deployment. Conduct feature engineering on various data sources to build and enrich feature store Fine tune open source LLM to detect anomalous user behavior Leverage Generative AI to perform RAG for helping improve Cyber investigation efficiency As a member of the CTAR team, you will work closely with other data scientists and data engineers to build, design, engineer, and develop analytical software and services that deliver security functionality and improve security efficiency and capabilities through automation. Assist in shaping overall direction, life-cycle management, and leadership for Information Security architecture and technology related to Visa. Communicate clean and persuasive data directly to end users, leadership, and other stakeholders, technical and non-technical. This is a hybrid position. Hybrid employees can alternate time between both remote and office. Employees in hybrid roles are expected to work from the office 2-3 set days a week (determined by leadership/site), with a general guidepost of being in the office 50% or more of the time based on business needs. Qualifications Basic Qualifications: •2+ years of relevant work experience and a Bachelors degree, OR 5+ years of relevant work experience Preferred Qualifications: •3 or more years of work experience with a Bachelor’s Degree or more than 2 years of work experience with an Advanced Degree (e.g. Masters, MBA, JD, MD) •Solid background and hands on experiences with building Machine learning, deep learning and AI models •Experience with Generative AI/LLM •Excellent understanding of algorithms and data structures and proficiency in Python and SQL. •Experience working with large datasets using tools and Hadoop, Spark, or Hive •Excellent analytic and problem-solving capability combined with ambition to solve hard problems •Strong communications skills and ability to collaborate •Highly driven, resourceful and results oriented •Good team player and excellent interpersonal skills •Demonstrated ability to lead and navigate through ambiguity

Job Role: Generative AI Engineer Intern Company: Growhut Technologies Private Limited Job Type: Full-Time Internship Location: Remote Stipend: INR 15,000 - 20,000 per month About Growhut At Growhut, we’re transforming industries with innovative AI solutions. Join our dynamic team to shape the future of technology and redefine possibilities through cutting-edge AI. The Role As a Generative AI Engineer Intern, you will work on groundbreaking AI projects, leveraging state-of-the-art tools and models to solve real-world challenges. What You’ll Do: Learn and experiment with cutting-edge Generative AI models, including GPT-4, PaLM, and Stable Diffusion, to create transformative applications. Assist in developing innovative AI solutions blending language, vision, and audio. Explore transformer architectures and contribute to optimizing them for impactful applications. Gain experience in prompt engineering and few-shot learning to unlock the potential of large language models. Support the team in building scalable inference systems for real-world applications. Collaborate on research initiatives and contribute to new techniques in controllable generation and multi-modal AI systems. Technical Requirements We’re looking for motivated individuals eager to learn and grow in the field of AI. The ideal candidate should have: Basic familiarity with Generative AI models (e.g., GPT-4, Stable Diffusion). Understanding of foundational AI concepts, including transformers and attention mechanisms. Experience with Agentic workflows and working with Conversational AI . Familiarity with LiveKit , AWS (including Lambda functions ), Google Cloud Platform (GCP), and Vertex AI . Interest in prompt engineering and few-shot learning techniques. Familiarity with programming languages like Python and frameworks like PyTorch or TensorFlow. Strong problem-solving skills and a keen interest in AI research. Why Growhut? At Growhut, we offer more than just an internship - we provide an opportunity to shape the future of AI. Here’s what sets us apart: Work on diverse, cutting-edge projects that will challenge and inspire you. Be part of a fast-growing company where your impact is felt immediately. Collaborate with a team of brilliant minds, pushing each other to new heights. The Growhut Difference At Growhut, we believe in AI’s power to change the world. We’re not just riding the wave of the future—we’re creating it. Every day, you’ll be able to work on projects that matter, solving real problems for real people. We’re looking for someone who is eager to learn, excited to take on challenges, and ready to contribute to groundbreaking AI innovations. If you’re ready to kickstart your career in AI, apply now , and let’s reshape the future together!

AI/ML ENGINEER Who We Are? Cleantech Industry Resources accelerates United States solar, battery storage and EV projects by providing turnkey development as a service including 100% internal systems engineering. The company deploys a leading team that spun out of the largest solar power producer in the world. This team operates within a sophisticated suite of software to support projects from land origination, through to commercial operation. Location Chennai What We Offer Opportunity to join a top-notch, collaborative team of professionals Fantastic team environment and collaborative culture Professional development opportunities to grow into an industry leader Medical Insurance for the employee and family Spot Recognition bonus for exceptional performance Long Term Incentive policy Regular team outings, events, and activities to foster a positive work environment Our Commitment to Diversity At CIR, we are dedicated to nurturing a diverse and equitable workforce that truly reflects our community. We deeply value each person’s unique perspective, skills, and experiences. CIR embraces all individuals, regardless of race, religion, sexual orientation, gender identity, age, or nationality. We are steadfast in our commitment to fostering a just and inclusive world through intentional policies and actions. Your individuality enriches our collective strength, and we strive to ensure everyone feels respected, valued, and empowered. Position Summary We are looking for an AI/ML Engineer to build and optimize machine learning models for GIS-based spatial analysis and data-driven decision-making. This role involves working on geospatial AI models, data pipelines, and Retrieval-Augmented Generation (RAG)-based applications for zoning, county sentiment analysis, and regulatory insights. The engineer will also work closely with the data team, leading efforts in data curation and building robust data pipelines to collect, preprocess, and analyse extensive datasets from various geospatial and regulatory sources to generate automated reports and insights. Core Responsibilities Machine Learning for GIS & Spatial Analysis: Develop and deploy ML models for geospatial data processing, forecasting, and automated GIS insights. Work with large-scale geospatial datasets (e.g., satellite imagery, shapefiles, raster/vector data). Create AI models for land classification, feature detection, and geospatial pattern analysis. Optimize spatial data pipelines and build predictive models for environmental and energy sector applications. Retrieval-Augmented Generation (RAG) & NLP Development: Develop RAG-based AI applications to extract insights from zoning, permitting, and regulatory documents. Build LLM-based applications for zoning law interpretation, county sentiment analysis, and compliance predictions. Implement document retrieval and summarization techniques for legal, policy, and energy development reports. Data Engineering & Pipeline Development: Lead the creation of ETL pipelines to collect and preprocess geospatial data for ML model training. Work with PostGIS, PostgreSQL, and cloud storage to manage structured and unstructured data. Collaborate with the data team to design and implement efficient data processing and storage solutions. AI Model Optimization & Deployment: Fine-tune LLMs for domain-specific applications in renewable energy and urban planning. Deploy AI models using cloud-based MLOps frameworks (AWS, GCP, Azure). Optimize ML model inference for real-time GIS applications and geospatial data analysis. Collaboration & Continuous Improvement: Work with cross-functional teams to ensure seamless AI integration with existing business processes. Engage in knowledge sharing and mentoring within the company. Stay updated with latest advancements in AI, GIS, and NLP to improve existing models and solutions. Education Requirements Master’s in Computer Science, Data Science, Machine Learning, Geostatistics, or related fields. Technical Skills and Experience Software Proficiency: Programming: Python (TensorFlow, PyTorch, scikit-learn, pandas, NumPy), SQL. Machine Learning & AI: Deep learning, NLP, retrieval-based AI, geospatial AI, predictive modeling. GIS & Spatial Data Processing: Experience with PostGIS, GDAL, GeoPandas, QGIS, Google Earth Engine. LLM & RAG Development: Experience in fine-tuning LLMs, retrieval models, vector databases (FAISS, Weaviate). Cloud & MLOps: AWS/GCP/Azure, Docker, Kubernetes, MLflow, FastAPI. Big Data Processing: Experience with large-scale data mining, data annotation, and knowledge graph techniques. Database & Storage: PostgreSQL, NoSQL, vector databases, cloud storage solutions. Communication: Strong ability to explain complex AI/ML concepts to non-technical stakeholders. Project Management: Design experience in projects from conception to implementation. Ability to coordinate with other engineers and stakeholders. Renewable Energy Systems: Understanding of solar energy systems and their integration into existing infrastructure Experience 2-4 years of experience Experience in developing AI for energy sector, urban planning, or environmental analysis. Strong understanding of potential prediction, zoning laws, and regulatory compliance AI applications. Familiarity with spatiotemporal ML models and satellite-based geospatial analytics. Psychosocial Skills /Human Skills/Behavioural Skills Strong analytical, organizational, and problem-solving skills. Management experience a plus. Must be a go-getter with an enterprising attitude A self-starter, able to demonstrate high levels of initiative and motivation Entrepreneurial mindset with the ability to take ideas and run with them from concept to conclusion. Technical understanding of clean energy business processes Exceptional verbal and writing communication skills with superiors, peers, partners, and other stakeholders. Excellent interpersonal skills while managing multiple priorities in a fast-paced and ever-changing environment. Physical Demands The physical demands described here are representative of those that must be met by an employee to successfully perform the essential functions of this job. The physical demands of this job require an individual to be able to work at a computer for most of the day, be able to participate in conference calls and travel to team retreats on a time-to-time basis. Reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions. Work Conditions The work environment is usually quiet (normal city traffic noises are common), a blend of artificial and natural light, temperate and generally supports a collaborative work environment. Reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions. Equal Opportunity Employer At Cleantech Industry Resources, we embrace diversity and uphold a strong dedication to establishing an all-encompassing atmosphere for both our staff and associates. Our choices in employment are free from any bias related to race, creed, nationality, ethnicity, gender, sexual orientation, gender identity, gender expression, age, physical limitations, veteran status, or any other legally safeguarded attributes. Being an integral part of Cleantech Industry Resources means you can expect to be immersed in a realm of professional possibilities within a culture that nurtures teamwork, adaptability, and the embracing of all.

Exp : 15yrs to 23yrs Primary skills :- Vision AI Solution, Nvidia, Computer Vision, Media, Open Stack. Key Responsibilities Define and lead the end-to-end technical architecture for vision-based AI systems across edge and cloud. Design and optimize large-scale video analytics pipelines using NVIDIA DeepStream, TensorRT, and Triton Inference Server. Architect distributed AI systems, including model training, deployment, inferencing, monitoring, and continuous learning. Collaborate with product, research, and engineering teams to translate business requirements into scalable AI solutions. Lead efforts in model optimization (quantization, pruning, distillation) for real-time performance on devices like Jetson Orin/Xavier. Drive the integration of multi-modal AI (vision + language, 3D, audio) where applicable. Guide platform choices (e.g., edge AI vs cloud AI trade-offs), ensuring cost-performance balance. Mentor senior engineers and promote best practices in MLOps, system reliability, and AI observability. Stay current with emerging technologies (e.g., NeRF, Diffusion Models, Vision Transformers, synthetic data). Contribute to internal innovation strategy, including IP generation, publications, and external presentations. ________________________________________ 🛠️ Required Technical Skills Deep expertise in computer vision, deep learning, and multi-modal AI. Proven hands-on experience with: NVIDIA Jetson, DeepStream SDK, TensorRT, Triton Inference Server TAO Toolkit, Isaac SDK, CUDA, cuDNN Strong in PyTorch, TensorFlow, OpenCV, GStreamer, and GPU-accelerated pipelines. Experience deploying vision AI models at large scale (e.g., 1000+ cameras/devices or multi-GPU clusters). Skilled in cloud-native ML infrastructure: Docker, Kubernetes, CI/CD, MLflow, Seldon, Airflow Proficiency in Python, C++, CUDA (or PyCUDA), and scripting. Familiar with 3D vision, synthetic data pipelines, and generative models (e.g., SAM, NeRF, Diffusion). Experience in multi modal (LVM/VLM), SLMs, small LVM/ VLM, Time series Gen AI models, Agentic AI, LLMOps/Edge LLMOps, Guardrails, Security in Gen AI, YOLO/Vision Transformers ________________________________________ 🤝 Soft Skills & Leadership 10+ years in AI/ML/Computer Vision, with 8+ years in technical leadership or architect roles Strong leadership skills with experience mentoring technical teams and driving innovation. Excellent communicator with the ability to engage stakeholders across engineering, product, and business. Strategic thinker with a practical mindset—able to balance innovation with production-readiness. Experience interfacing with enterprise customers, researchers, and hardware partners. ________________________________________ 🧩 Preferred Qualifications MS or PhD in Computer Vision, Machine Learning, Robotics, or a related technical field ( Added Advantage ) Experience with NVIDIA Omniverse, Clara, or MONAI for healthcare or simulation environments. Experience in domains like smart cities, robotics, retail analytics, or medical imaging. Contributions to open-source projects or technical publications. Certifications: NVIDIA Jetson Developer, AWS/GCP AI/ML Certifications.

Primary skill :- NVIDIA Solution Architect, GEN / AI Architect, Azure or AWS cloud. Relevant Exp :- NVIDIA ( 2 to 3 yrs ) Location :- Chennai / Noida. As an NVIDIA Generative AI Solution Architect at , you will lead the design, development, and deployment of AI solutions leveraging NVIDIA’s Edge AI, Computer Vision, Generative AI, and Metropolis technologies . You will collaborate with cross-functional teams and customers to architect scalable, high-performance AI systems integrating real-time computer vision, generative AI workflows, and industrial digital twins on edge, cloud, and metaverse platforms. Key Responsibilities Architect and deliver end-to-end AI solutions using NVIDIA’s AI Enterprise software, NeMo framework, Triton Inference Server, and GPU-accelerated platforms. Design and implement AI pipelines optimized for edge devices (NVIDIA Jetson, Clara), cloud infrastructure (AWS, Azure, GCP), and data centers (NVIDIA DGX). Develop and showcase proof-of-concept solutions using large language models (LLMs), retrieval-augmented generation (RAG), and advanced computer vision models for object detection, segmentation, and video analytics. Utilize NVIDIA Metropolis platform capabilities to architect AI-powered video analytics and smart city solutions, leveraging edge-to-cloud pipelines for real-time insights and automation. Optimize AI inference workloads using CUDA, TensorRT, mixed precision, and model quantization to meet stringent latency and throughput SLAs. Collaborate with company engineering, product, and client teams to embed NVIDIA AI technologies into enterprise workflows and industrial applications. Provide technical leadership, training, and mentorship on NVIDIA SDKs, AI best practices, and solution deployment strategies. Stay abreast of NVIDIA’s product roadmap, AI research trends, and industrial AI innovations to drive continuous solution improvement. Support customer engagements including technical workshops, solution demonstrations, and architectural reviews. Ensure adherence to data privacy, security, and ethical AI standards throughout the solution lifecycle. Required Qualifications Bachelor’s or Master’s degree in Computer Science, Electrical Engineering, or related technical field. 5+ years of experience architecting and deploying AI/ML solutions with strong expertise in NVIDIA AI platforms (NeMo, Triton, CUDA, TensorRT). Proven experience with generative AI technologies including large language models, prompt engineering, and RAG workflows. Strong background in computer vision applications, including object detection, segmentation, and video analytics frameworks. Hands-on experience deploying AI solutions on edge devices (NVIDIA Jetson, Clara), cloud platforms (Azure, AWS, GCP), and data center GPU infrastructure. Familiarity with NVIDIA Metropolis platform for AI-powered video analytics and smart infrastructure solutions. Proficiency in Python, C++, and deep learning frameworks such as PyTorch or TensorFlow. Experience with container orchestration (Kubernetes, Docker) and MLOps practices including CI/CD pipelines for AI workloads. Excellent communication skills for engaging technical teams and business stakeholders. Willingness to travel up to 15% for client and NVIDIA events. Preferred Skills Experience optimizing AI inference with TensorRT, mixed precision, and model quantization. Knowledge of AI ethics, bias mitigation, and responsible AI principles. Prior experience in industrial, manufacturing, smart cities, or healthcare domains. Certifications related to NVIDIA AI technologies or cloud platforms (AWS, Azure, GCP). Experience working in global, cross-cultural teams.

Principal Data Scientist Experience : 14-16 years Job Summary We are seeking a highly experienced AI Lead - Principal Data Scientist to spearhead the delivery of multiple AI and machine learning projects across industries such as supply chain, logistics, pricing, manufacturing, and workforce planning. This role combines deep hands-on expertise in AI/ML/Gen AI (50%) with strategic leadership and cross-functional stakeholder management. You will lead enterprise AI solutions from concept to production, architect scalable cloud-native platforms, and collaborate with business and technology teams to deliver measurable business outcomes. Key Responsibilities Technical Leadership & Solutioning : Design, build, and deploy advanced AI, machine learning, deep learning, and Gen AI solutions using Python, Scikit-learn, TensorFlow/PyTorch, and LangChain/OpenAI APIs. Architect and implement end-to-end AI systems including data ingestion, preprocessing, model training, validation, and deployment. Develop modular, reusable components and APIs (FastAPI/Flask) for inference and integration with digital applications. Lead cloud-native development on AWS, Azure, or GCP for scalable deployment of AI models and pipelines. Project & Delivery Ownership Manage the delivery of multiple concurrent AI/ML/Gen AI initiatives, ensuring quality, timeliness, and business alignment. Define technical roadmap, sprint plans, and milestone goals; track delivery KPIs and model performance in production. Guide agile teams through best practices in model lifecycle management, DevOps/MLOps, and reusable IP development. Business Engagement & Techno-Functional Consulting Act as the techno-functional bridge between business and engineering teams to translate high-level problems into AI/ML use cases. Conduct business value assessments, requirement workshops, and stakeholder reviews. Drive adoption by presenting explainable AI results using visual storytelling and decision support tools. Team Enablement & Innovation Mentor and upskill junior data scientists and engineers in best practices, new AI trends, and real-world problem-solving. Stay current with the latest trends in Generative AI, LLMs, Vision AI, and responsible AI practices. Contribute to internal frameworks, accelerators, and reusable artifacts for faster go-to-market. Required Skills & Qualifications Bachelor's or Master's in Computer Science, AI/ML, Data Science, or related quantitative field. 10-13 years of experience in delivering AI/ML solutions at scale with at least 5 years in a lead or principal role. Hands-on expertise in Python, ML/DL frameworks (TensorFlow, PyTorch, Scikit-learn) and Generative AI (OpenAI, Llama, LangChain). Strong cloud development experience with AWS, GCP, or Azure, including AI/ML services and containerized deployments. Experience deploying models in production via APIs and integrating with enterprise applications. Excellent communication, stakeholder management, and problem-solving skills. Preferred Qualifications Experience in Generative AI (LLMs, prompt engineering, RAG pipelines). Familiarity with MLOps tools (MLflow, Airflow, DVC, Kubeflow). Working knowledge of data engineering workflows, feature stores, and streaming/batch data pipelines. Exposure to data visualization tools like Streamlit, Dash, or Power BI for presenting insights. Certifications in cloud (AWS/GCP/Azure), AI/ML, or data science. (ref:hirist.tech)

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.

When you join Verizon You want more out of a career. A place to share your ideas freely even if theyre daring or different. Where the true you can learn, grow, and thrive. At Verizon, we power and empower how people live, work and play by connecting them to what brings them joy. We do what we love driving innovation, creativity, and impact in the world. Our V Team is a community of people who anticipate, lead, and believe that listening is where learning begins. In crisis and in celebration, we come together lifting our communities and building trust in how we show up, everywhere & always. Want in? Join the #VTeamLife. What Youll Be Doing... Join Verizon as we continue to grow our industry-leading network to improve the ways people, businesses, and things connect. We are looking for an experienced, talented and motivated AI&ML Engineer to lead AI Industrialization for Verizon. You will also serve as a subject matter expert regarding the latest industry knowledge to improve the Home Product and solutions and/or processes related to Machine Learning, Deep Learning, Responsible AI, Gen AI, Natural Language Processing, Computer Vision and other AI practices. Deploying machine learning models - On Prem, Cloud and Kubernetes environments Driving data-derived insights across the business domain by developing advanced statistical models, machine learning algorithms and computational algorithms based on business initiatives. Creating and implementing data and ML pipelines for model inference, both in real-time and in batches. Architecting, designing, and implementing large-scale AI/ML systems in a production environment. Monitor the performance of data pipelines and make improvements as necessary What were looking for... You have strong analytical skills and are eager to work in a collaborative environment with global teams to drive ML applications in business problems, develop end-to-end analytical solutions, and communicate insights and findings to leadership. You work independently and are always willing to learn new technologies. You thrive in a dynamic environment and can interact with various partners and multi-functional teams to implement data science-driven business solutions. You'll Need To Have Bachelor's degree with four or more years of relevant work experience. Expertise in advanced analytics/ predictive modelling in a consulting role. Experience with all phases of end-to-end Analytics project Hands-on programming expertise in Python (with libraries like NumPy, Pandas, Scikit-learn, TensorFlow, PyTorch), R (for specific data analysis tasks) Knowledge of Machine Learning Algorithms - Linear Regression, Logistic Regression, Decision Trees, Random Forests, Support Vector Machines (SVMs), Neural Networks (Deep Learning), Bayesian Networks Data Engineering - Data Cleaning and Preprocessing, Feature Engineering, Data Transformation, Data Visualization Cloud Platforms - AWS SageMaker, Azure Machine Learning, Cloud AI Platform Even better if you have one or more of the following: Advanced degree in Computer Science, Data Science, Machine Learning, or a related field. Knowledge on Home domain with key areas like Smart Home, Digital security and wellbeing Experience with stream-processing systems: Spark-Streaming, Storm etc. #TPDNONCDIO Where youll be working In this hybrid role, you'll have a defined work location that includes work from home and assigned office days set by your manager. Scheduled Weekly Hours 40 Equal Employment Opportunity Verizon is an equal opportunity employer. We evaluate qualified applicants without regard to race, gender, disability or any other legally protected characteristics. Locations Hyderabad, India Chennai, India

Welcome to Radin Health A premier Healthcare IT Software as a Service (SaaS) provider specializing in revolutionizing radiology workflow processes. Our cloud-based solutions encompass Radiology Information Systems (RIS), Picture Archiving and Communication Systems (PACS), Voice Dictation (Dictation AI) and Radiologist Workflow Management (RADIN Select), all powered by Artificial Intelligence. We are an innovative, forward-thinking Company with AI-Powered Solutions. Join Our Team! We Are Looking for Talent We are seeking a highly skilled AI Engineer with proven experience in healthcare document intelligence. You will lead the development and optimization of machine learning models for document classification and OCR-based data extraction , helping us extract structured data from prescriptions, insurance cards, consent forms, orders, and other medical records. You will be part of a fast-paced, cross-functional team working to integrate AI seamlessly into healthcare operations while maintaining the highest standards of accuracy, security, and compliance. Key Responsibilities Model Development: Design, train, and deploy ML/DL models for classifying healthcare documents and extracting structured data (e.g., patient info, insurance details, physician names, procedures). OCR Integration & Tuning: Work with OCR engines like Tesseract, AWS Textract, or Google Vision to extract text from scanned images and PDFs, enhancing accuracy via post-processing and pre-processing techniques. Document Classification: Build and refine document classification models using supervised learning and NLP techniques, with real-world noisy healthcare data. Data Labeling & Annotation: Create tools and workflows for large-scale labeling; collaborate with clinical experts and data annotators to improve model precision. Model Evaluation & Improvement: Measure model performance using precision, recall, F1 scores, and deploy improvements based on real-world production feedback. Pipeline Development: Build scalable ML pipelines for training, validation, inference, and monitoring using frameworks like PyTorch, TensorFlow, and MLFlow. Collaboration: Work closely with backend engineers, product managers, and QA teams to integrate models into healthcare products and workflows. Required Skills & Qualifications Bachelor's or Master’s in Computer Science, AI, Data Science, or related field. 7+ years experience in machine learning, with at least 3 years in healthcare AI applications. Strong experience with OCR technologies (Tesseract, AWS Textract, Azure Form Recognizer, Google Vision API). Proven track record in training and deploying classification models for healthcare documents. Experience with Python (NumPy, Pandas, Scikit-learn), deep learning frameworks (PyTorch, TensorFlow), and NLP libraries (spaCy, Hugging Face, etc.). Understanding of HIPAA-compliant data handling and healthcare terminology. Familiarity with real-world document types such as referrals, AOBs, insurance cards, and physician notes. Preferred Qualifications Experience working with noisy scanned documents and handwritten text. Exposure to EHR/EMR systems and HL7/FHIR integration. Knowledge of labeling tools like Label Studio or Prodigy. Experience with active learning or human-in-the-loop systems. Contributions to healthcare AI research or open-source projects.

About The Role We’re hiring a Senior AI Engineer with expertise in Computer Vision, document understanding, and voice AI to help build the brains behind our AI agents. You’ll work on the two core components of our AI agents – first, the core perception systems that extract structured insights from messy, real-world freight documents—handwritten, scanned, distorted, or multi-page – and second, our AI agents for email and voice communications between freight entities. You will do a lot of prompt engineering, fine-tuning LLMs, building large-scale document classification and entity extraction models, communication understanding, intent classification, and voice AI – your code will be at the heart of automating financial decision-making in freight. You’ll collaborate closely with the backend and product teams to bring AI models to life in production environments and continuously improve performance in the wild. What You’ll Do 👉🏼 Build and fine-tune AI models for document classification, OCR, entity recognition, and layout parsing 👉🏼 Build AI agents for email and phone communications between different freight accounting parties – payer and payee 👉🏼 Develop scalable pipelines for pre-processing, training, inference, and feedback loops 👉🏼 Evaluate and integrate VLMs👉🏼 Annotate, clean, and curate diverse freight documents for robust model performance 👉🏼Build training, evaluation, and test datasets 👉🏼Identify issues identified in production data and fix them asap 👉🏼Iterate on improving existing and new AI stack 👉🏼 Productionize AI models as part of Lighthouz’s intelligent automation stack 👉🏼 Collaborate with backend engineers to integrate model outputs into document, email, and voice workflows 👉🏼 Continuously monitor and improve model performance in real-world conditions What We’re Looking For 👉🏼 3–6 years experience in ML or AI roles, preferably focused on computer vision or document AI 👉🏼 Strong foundation in deep learning frameworks (e.g., PyTorch, TensorFlow) 👉🏼 Experience in fine-tuning VLMs and LLMs 👉🏼 Experience in voice AI 👉🏼 Experience with document/image OCR, visual transformers, and multimodal models 👉🏼 Proficiency in Python and common ML tooling (e.g., Hugging Face, OpenCV, spaCy) 👉🏼 Hands-on experience training and deploying models in production 👉🏼 Strong problem-solving skills and a builder mindset—you move fast and iterate faster 👉🏼 Comfortable working with ambiguity and evolving datasets 👉🏼 Willingness to work long hours Nice to Have 👉🏼 Familiarity with freight, logistics, or fintech workflows 👉🏼 Experience with AWS, Azure, or GCP-based ML infrastructure 👉🏼 Exposure to RAG pipelines, foundation models, or vector search systems 👉🏼 Knowledge of document layout understanding (e.g., Donut, LayoutLM, PubLayNet) 👉🏼 Background in building secure, production-grade ML services What We Offer 💰 Competitive salary 🌎 Fully remote 🛠️ High ownership, zero bureaucracy—help shape our AI stack from day one 🚀 Work on impactful real-world problems that blend AI and automation at scale Skills: communication understanding,node.js,rest apis,fine-tuning llms,voice ai,large-scale document classification,hugging face,spacy,nosql,kubernetes,document understanding,docker,postgresql,aws,ml tooling,production model deployment,sql,opencv,api,entity extraction,frontend javascript tech,intent classification,microservices,backend development,prompt engineering,deep learning frameworks,flask,ai/ml workflows,python,computer vision,ocr,event-driven architectures,mongodb

About The Role We’re hiring a Senior AI Engineer with expertise in Computer Vision, document understanding, and voice AI to help build the brains behind our AI agents. You’ll work on the two core components of our AI agents – first, the core perception systems that extract structured insights from messy, real-world freight documents—handwritten, scanned, distorted, or multi-page – and second, our AI agents for email and voice communications between freight entities. You will do a lot of prompt engineering, fine-tuning LLMs, building large-scale document classification and entity extraction models, communication understanding, intent classification, and voice AI – your code will be at the heart of automating financial decision-making in freight. You’ll collaborate closely with the backend and product teams to bring AI models to life in production environments and continuously improve performance in the wild. What You’ll Do 👉🏼 Build and fine-tune AI models for document classification, OCR, entity recognition, and layout parsing 👉🏼 Build AI agents for email and phone communications between different freight accounting parties – payer and payee 👉🏼 Develop scalable pipelines for pre-processing, training, inference, and feedback loops 👉🏼 Evaluate and integrate VLMs👉🏼 Annotate, clean, and curate diverse freight documents for robust model performance 👉🏼Build training, evaluation, and test datasets 👉🏼Identify issues identified in production data and fix them asap 👉🏼Iterate on improving existing and new AI stack 👉🏼 Productionize AI models as part of Lighthouz’s intelligent automation stack 👉🏼 Collaborate with backend engineers to integrate model outputs into document, email, and voice workflows 👉🏼 Continuously monitor and improve model performance in real-world conditions What We’re Looking For 👉🏼 3–6 years experience in ML or AI roles, preferably focused on computer vision or document AI 👉🏼 Strong foundation in deep learning frameworks (e.g., PyTorch, TensorFlow) 👉🏼 Experience in fine-tuning VLMs and LLMs 👉🏼 Experience in voice AI 👉🏼 Experience with document/image OCR, visual transformers, and multimodal models 👉🏼 Proficiency in Python and common ML tooling (e.g., Hugging Face, OpenCV, spaCy) 👉🏼 Hands-on experience training and deploying models in production 👉🏼 Strong problem-solving skills and a builder mindset—you move fast and iterate faster 👉🏼 Comfortable working with ambiguity and evolving datasets 👉🏼 Willingness to work long hours Nice to Have 👉🏼 Familiarity with freight, logistics, or fintech workflows 👉🏼 Experience with AWS, Azure, or GCP-based ML infrastructure 👉🏼 Exposure to RAG pipelines, foundation models, or vector search systems 👉🏼 Knowledge of document layout understanding (e.g., Donut, LayoutLM, PubLayNet) 👉🏼 Background in building secure, production-grade ML services What We Offer 💰 Competitive salary 🌎 Fully remote 🛠️ High ownership, zero bureaucracy—help shape our AI stack from day one 🚀 Work on impactful real-world problems that blend AI and automation at scale Skills: node.js,rest apis,large-scale document classification,nosql,ml tooling,postgresql,production model deployment,sql,opencv,frontend javascript tech,intent classification,prompt engineering,deep learning frameworks,python,deep learning frameworks (pytorch, tensorflow),computer vision,event-driven architectures,communication understanding,fine-tuning llms,voice ai,hugging face,spacy,kubernetes,document understanding,docker,aws,api,entity extraction,microservices,backend development,multimodal models,flask,ai/ml workflows,ocr,document classification,mongodb

Role Overview As a Backend Developer at LearnTube.ai, you will ship the backbone that powers 2.3 million learners in 64 countries—owning APIs that crunch 1 billion learning events & the AI that supports it with <200 ms latency. What You'll Do At LearnTube, we’re pushing the boundaries of Generative AI to revolutionize how the world learns. As a Backend Engineer, your roles and responsibilities will include: Ship Micro-services – Build FastAPI services that handle ≈ 800 req/s today and will triple within a year (sub-200 ms p95). Power Real-Time Learning – Drive the quiz-scoring & AI-tutor engines that crunch millions of events daily. Design for Scale & Safety – Model data (Postgres, Mongo, Redis, SQS) and craft modular, secure back-end components from scratch. Deploy Globally – Roll out Dockerised services behind NGINX on AWS (EC2, S3, SQS) and GCP (GKE) via Kubernetes. Automate Releases – GitLab CI/CD + blue-green / canary = multiple safe prod deploys each week. Own Reliability – Instrument with Prometheus / Grafana, chase 99.9 % uptime, trim infra spend. Expose Gen-AI at Scale – Publish LLM inference & vector-search endpoints in partnership with the AI team. Ship Fast, Learn Fast – Work with founders, PMs, and designers in weekly ship rooms; take a feature from Figma to prod in What makes you a great fit? Must-Haves 2+ yrs Python back-end experience (FastAPI) Strong with Docker & container orchestration Hands-on with GitLab CI/CD, AWS (EC2, S3, SQS) or GCP (GKE / Compute) in production SQL/NoSQL (Postgres, MongoDB) + You’ve built systems from scratch & have solid system-design fundamentals Nice-to-Haves k8s at scale, Terraform, Experience with AI/ML inference services (LLMs, vector DBs) Go / Rust for high-perf services Observability: Prometheus, Grafana, OpenTelemetry About Us At LearnTube, we’re on a mission to make learning accessible, affordable, and engaging for millions of learners globally. Using Generative AI, we transform scattered internet content into dynamic, goal-driven courses with: AI-powered tutors that teach live, solve doubts in real time, and provide instant feedback. Seamless delivery through WhatsApp, mobile apps, and the web, with over 1.4 million learners across 64 countries. Meet The Founders LearnTube was founded by Shronit Ladhani and Gargi Ruparelia, who bring deep expertise in product development and ed-tech innovation. Shronit, a TEDx speaker, is an advocate for disrupting traditional learning, while Gargi’s focus on scalable AI solutions drives our mission to build an AI-first company that empowers learners to achieve career outcomes. We’re proud to be recognised by Google as a Top 20 AI Startup and are part of their 2024 Startups Accelerator: AI First Program, giving us access to cutting-edge technology, credits, and mentorship from industry leaders. Why Work With Us? Role At LearnTube, we believe in creating a work environment that’s as transformative as the products we build. Here’s why this role is an incredible opportunity: Cutting-Edge Technology: You’ll work on state-of-the-art generative AI applications, leveraging the latest advancements in LLMs, multimodal AI, and real-time systems. Autonomy and Ownership: Experience unparalleled flexibility and independence in a role where you’ll own high-impact projects from ideation to deployment. Rapid Growth: Accelerate your career by working on impactful projects that pack three years of learning and growth into one. Founder and Advisor Access: Collaborate directly with founders and industry experts, including the CTO of Inflection AI, to build transformative solutions. Team Culture: Join a close-knit team of high-performing engineers and innovators, where every voice matters, and Monday morning meetings are something to look forward to. Mission-Driven Impact: Be part of a company that’s redefining education for millions of learners and making AI accessible to everyone. Skills:- Python, FastAPI, Amazon Web Services (AWS), MongoDB, CI/CD, Kubernetes, Docker, Git, PostgreSQL and NOSQL Databases

CWX is looking for a dynamic SENIOR AI/ML ENGINEER to become a vital part of our vibrant PROFESSIONAL SERVICES TEAM , working on-site in Hyderabad . Join the energy and be part of the momentum! At CloudWerx, we're looking for a Senior AI/ML Engineer to lead the design, development, and deployment of tailored AI/ML solutions for our clients. In this role, you'll work closely with clients to understand their business challenges and build innovative, scalable, and cost-effective solutions using tools like Google Cloud Platform (GCP), Vertex AI, Python, PyTorch, LangChain, and more. You'll play a key role in translating real-world problems into robust machine learning architectures, with a strong focus on Generative AI, multi-agent systems, and modern MLOps practices. From data preparation and ensuring data integrity to building and optimizing models, you'll be hands-on across the entire ML lifecycle — all while ensuring seamless deployment and scaling using cloud-native infrastructure. Clear communication will be essential as you engage with both technical teams and business stakeholders, making complex AI concepts understandable and actionable. Your deep expertise in model selection, optimization, and deployment will help deliver high-performing solutions tailored to client needs. We're also looking for someone who stays ahead of the curve — someone who's constantly learning and experimenting with the latest developments in generative AI, LLMs, and cloud technologies. Your curiosity and drive will help push the boundaries of what's possible and fuel the success of the solutions we deliver. This is a fantastic opportunity to join a fast-growing, engineering-led cloud consulting company that tackles some of the toughest challenges in the industry. At CloudWerx, every team member brings something unique to the table, and we foster a supportive environment that helps people do their best work. Our goal is simple: to be the best at what we do and help our clients accelerate their businesses through world-class cloud solutions. This role is an immediate full time position. Insight on your impact Conceptualize, Prototype, and Implement AI Solutions: Design and deploy advanced AI solutions using large language models (LLMs), diffusion models, and multimodal AI systems by leveraging Google Cloud tools such as Vertex AI, AutoML, and AI Platform (Agent Builder). Implement Retrieval-Augmented Generation (RAG) pipelines for chatbots and assistants, and create domain-specific transformers for NLP, vision, and cross-modal applications. Utilize Document AI, Translation AI, and Vision AI to develop full-stack, multimodal enterprise applications. Technical Expertise: models via LoRA, QLoRA, RLHF, and Dreambooth. Build multi-agent systems using Agent Development Kit (ADK), Agent-to-Agent (A2A) Protocol, and Model Context Protocol (MCP). Provide thought leadership on best practices, architecture patterns, and technical decisions across LLMs, generative AI, and custom ML pipelines, tailored to each client's unique business needs. Stakeholder Communication: Effectively communicate complex AI/ML concepts, architectures, and solutions to business leaders, technical teams, and non-technical stakeholders. Present project roadmaps, performance metrics, and model validation strategies to C-level executives and guide organizations through AI transformation initiatives. Understand client analytics & modeling needs: Collaborate with clients to extract, analyze, and interpret both internal and external data sources. Design and operationalize data pipelines that support exploratory analysis and model development, enabling business-aligned data insights and AI solutions. Database Management: Work with structured (SQL/BigQuery) and unstructured (NoSQL/Firestore, Cloud Storage) data. Apply best practices in data quality, versioning, and integrity across datasets used for training, evaluation, and deployment of AI/ML models. Cloud Expertise: Architect and deploy cloud-native AI/ML solutions using Google Cloud services including Vertex AI, BigQuery ML, Cloud Functions, Cloud Run, and GKE Autopilot. Provide consulting on GCP service selection, infrastructure scaling, and deployment strategies aligned with client requirements. MLOps & DevOps: Lead the implementation of robust MLOps and LLMOps pipelines using TensorFlow Extended (TFX), Kubeflow, and Vertex AI Pipelines. Set up CI/CD workflows using Cloud Build and Artifact Registry, and deploy scalable inference endpoints through Cloud Run and Agent Engine. Establish automated retraining, drift detection, and monitoring strategies for production ML systems. Prompt Engineering and fine tuning: Apply advanced prompt engineering strategies (e.g., few-shot, in-context learning) to optimize LLM outputs. Fine-tune models using state-of-the-art techniques including LoRA, QLoRA, Dreambooth, ControlNet, and RLHF to enhance instruction-following and domain specificity of generative models. LLMs, Chatbots & Text Processing: Develop enterprise-grade chatbots and conversational agents using Retrieval-Augmented Generation (RAG), powered by both open-source and commercial LLMs. Build state-of-the-art generative solutions for tasks such as intelligent document understanding, summarization, and sentiment analysis. Implement LLMOps workflows for lifecycle management of large-scale language applications. Consistently Model and Promote Engineering Best Practices: Promote a culture of technical excellence by adhering to software engineering best practices including version control, reproducibility, structured documentation, Agile retrospectives, and continuous integration. Mentor junior engineers and establish guidelines for scalable, maintainable AI/ML development. Our Diversity and Inclusion Commitment At CloudWerx, we are dedicated to creating a workplace that values and celebrates diversity. We believe that a diverse and inclusive environment fosters innovation, collaboration, and mutual respect. We are committed to providing equal employment opportunities for all individuals, regardless of background, and actively promote diversity across all levels of our organization. We welcome all walks of life, as we are committed to building a team that embraces and mirrors a wide range of perspectives and identities. Join us in our journey toward a more inclusive and equitable workplace. Background Check Requirement All candidates for employment will be subject to pre-employment background screening for this position. All offers are contingent upon the successful completion of the background check. For additional information on the background check requirements and process, please reach out to us directly. Our Story CloudWerx is an engineering-focused cloud consulting firm born in Silicon Valley - in the heart of hyper-scale and innovative technology. In a cloud environment we help businesses looking to architect, migrate, optimize, secure or cut costs. Our team has unique experience working in some of the most complex cloud environments at scale and can help businesses accelerate with confidence.

At Lilly, we unite caring with discovery to make life better for people around the world. We are a global healthcare leader headquartered in Indianapolis, Indiana. Our employees around the world work to discover and bring life-changing medicines to those who need them, improve the understanding and management of disease, and give back to our communities through philanthropy and volunteerism. We give our best effort to our work, and we put people first. We’re looking for people who are determined to make life better for people around the world. Lilly’s Purpose At Lilly, we unite caring with discovery to make life better for people around the world. We are a global healthcare leader headquartered in Indianapolis, Indiana. Our 42,000+ employees across the globe work to discover and bring life-changing medicines to those who need them, improve the understanding and management of disease, and give back to our communities through philanthropy and volunteerism. We give our best effort to our work and put people first. Come build advanced software capabilities to accelerate our digital transformation and support Lilly’s evolution to be the leader in Pharma-tech! The Role The Software Product Engineering (SPE) organization is actively looking for a Senior Quality Engineer with strong hands-on experience in AI platform testing, chatbot testing, AI model validation, agents testing, AI test automation, and API testing . This is a highly specialized role focused on validating complex AI and ML systems and ensuring scalable, safe, and effective deployment of AI-based solutions. UI automation experience using tools like Selenium , Cypress , or Playwright is desirable as a secondary skill . What You’ll Be Doing You will drive quality engineering initiatives specifically focused on AI-powered platforms and solutions , including LLMs, chatbots, AI agents, and intelligent workflows. You’ll build robust test strategies and frameworks to validate data pipelines, model inference accuracy, prompt engineering, hallucination control, API contracts, and performance under real-world conditions. This role requires strong analytical and problem-solving skills, a deep understanding of AI systems testing, and the ability to collaborate across multidisciplinary teams such as SWE, SRE, ML Engineering, and Product. Key Responsibilities AI Platform & Model Testing (Primary Focus): Validate the behaviour and performance of AI/ML models, including LLMs, RAG pipelines, chatbots, and autonomous agents. Design and execute prompt evaluation, response accuracy, toxicity detection, and hallucination control test scenarios. Implement and enhance automated AI testing frameworks tailored to model versioning, retraining, and feedback loops. Ensure quality in human-in-the-loop (HITL) and continuous learning pipelines. API Testing: Conduct thorough API validation using Postman, REST Assured, or GraphQL, with a focus on AI service endpoints, inference APIs, and orchestrators. Build robust integration test suites to ensure seamless functionality between APIs and underlying AI systems. AI Test Automation: Build test harnesses to validate AI features through synthetic data, mock services, and model stubs. Integrate test suites into CI/CD pipelines to ensure continuous validation of AI behaviors. UI and Functional Test Automation (Secondary Focus): Support end-to-end automation of AI-powered applications using tools such as Selenium, Cypress, Playwright, and WebdriverIO. Automate critical user journeys involving AI-enabled decisions and interactions. Collaboration & Test Strategy: Work closely with ML Engineers, SREs, and Product Managers to translate model design into testable components. Monitor AI behavior in production using observability tools and adjust quality strategies based on live insights. Drive discussions on fairness, bias, explainability, and model drift. Agile & DevOps Integration: Participate in Agile ceremonies and actively contribute to sprint planning, test case reviews, and retrospectives. Collaborate with DevOps teams to embed AI testing into CI/CD workflows using tools like GitHub, Jenkins, and Azure DevOps. Required Technical Skills & Qualifications Bachelor’s or Master’s degree in Computer Science, Engineering, AI/ML, or a related field 6+ years of experience in Quality Engineering with at least 2 years in AI platform testing or model validation Hands-on experience in AI model testing, chatbot testing, prompt tuning, or agent workflows Proficiency in AI test automation and API testing tools (Postman, REST Assured, GraphQL) Working knowledge of Python, JavaScript, or TypeScript Experience integrating tests into CI/CD pipelines using GitHub, Jenkins, or Azure DevOps Knowledge of OpenAI, Bedrock, Anthropic, LangChain, RAG, and vector stores Understanding of LLM evaluation techniques, including metrics like BLEU, ROUGE, Toxicity Score, and RAGAs Preferred Qualifications Experience testing AI applications hosted in multi-geographical and cloud-native environments (e.g., AWS, GCP, Azure) Exposure to AI observability platforms such as Weights & Biases, Arize AI, or WhyLabs Understanding of prompt engineering, embedding quality, and tokenization behaviour Familiarity with security, performance, or accessibility testing Experience with AI governance frameworks and regulatory compliance (e.g., FDA, HIPAA in AI contexts) Lilly is dedicated to helping individuals with disabilities to actively engage in the workforce, ensuring equal opportunities when vying for positions. If you require accommodation to submit a resume for a position at Lilly, please complete the accommodation request form (https://careers.lilly.com/us/en/workplace-accommodation) for further assistance. Please note this is for individuals to request an accommodation as part of the application process and any other correspondence will not receive a response. Lilly does not discriminate on the basis of age, race, color, religion, gender, sexual orientation, gender identity, gender expression, national origin, protected veteran status, disability or any other legally protected status. #WeAreLilly

Full-time Job Description NIQ is looking for a Software Engineer to join our AI ML Engineering team. At NIQ, the Retail Measurement System (RMS) is a powerful analytics service that tracks product sales and market performance across a wide range of retail channels. It provides comprehensive, store-level data that helps businesses understand how their products are performing in the market, benchmark against competitors, and identify growth opportunities. Charlink and Jarvis models are used to predict product placements to its ideal hierarchy product tree. Learn more on the data driven approach to train models efficiently to predict placements based on Characteristics. Developing frontend applications to interact with ML models, integrating inference codes, and providing tools and patterns for enhancing our MLOps cycle. The ideal candidate has strong software design and programming experience, with some expertise in cloud computing, and big data technologies, and strong communication and management skills. You will be part of a diverse, flexible, and collaborative environment where you will be able to apply and develop your skills and knowledge working with unique data and exciting applications. Our Software Engineering platform is based in AngularJS, Java, React, Spring Boot, Typescript, Javascript, Sql and Snowflake, and we continue to adopt the best of breed in cloud-native, low-latency technologies. Who We Are Looking For You have a strong entrepreneurial spirit and a thirst to solve difficult challenges through innovation and creativity with a strong focus on results You have a passion for data and the insights it can deliver You are intellectually curious with a broad range of interests and hobbies You take ownership of your deliverables You have excellent analytical communication and interpersonal skills You have excellent communication skills with both technical and non-technical audiences You can work with distributed teams situated globally in different geographies You want to work in a small team with a start-up mentality You can work well under pressure, prioritize work and be well organized. Relish tackling new challenges, paying attention to details, and, ultimately, growing professionally. Responsibilities Design, develop, and maintain scalable web applications using AngularJS for the front end and Java (Spring Boot) for the backend Collaborate closely with cross-functional teams to translate business requirements into technical solutions Optimize application performance, usability, and responsiveness Conduct code reviews, write unit tests, and ensure adherence to coding standards Troubleshoot and resolve software defects and production issues Contribute to architecture and technical documentation Qualifications 3–5 years of experience as a full stack developer Proficient in AngularJS(Version 12+), Typescript, Java, Spring Framework (especially Spring Boot) Experience with RESTful APIs and microservices architecture Solid understanding of HTML, CSS, JavaScript, and responsive web design Familiarity with relational databases (e.g., MySQL, PostgreSQL) Hands-on experience with version control systems (e.g., GitHub) and CI/CD tools Strong problem-solving abilities and attention to detail 3 - 5+ years of relevant software engineering experience Minimum B.S. degree in Computer Science, Computer Engineering, Information Technology or related field Additional Information Enjoy a flexible and rewarding work environment with peer-to-peer recognition platforms. Recharge and revitalize with help of wellness plans made for you and your family. Plan your future with financial wellness tools. Stay relevant and upskill yourself with career development opportunities Our Benefits Flexible working environment Volunteer time off LinkedIn Learning Employee-Assistance-Program (EAP) About NIQ NIQ is the world’s leading consumer intelligence company, delivering the most complete understanding of consumer buying behavior and revealing new pathways to growth. In 2023, NIQ combined with GfK, bringing together the two industry leaders with unparalleled global reach. With a holistic retail read and the most comprehensive consumer insights—delivered with advanced analytics through state-of-the-art platforms—NIQ delivers the Full View™. NIQ is an Advent International portfolio company with operations in 100+ markets, covering more than 90% of the world’s population. For more information, visit NIQ.com Want to keep up with our latest updates? Follow us on: LinkedIn | Instagram | Twitter | Facebook Our commitment to Diversity, Equity, and Inclusion NIQ is committed to reflecting the diversity of the clients, communities, and markets we measure within our own workforce. We exist to count everyone and are on a mission to systematically embed inclusion and diversity into all aspects of our workforce, measurement, and products. We enthusiastically invite candidates who share that mission to join us. We are proud to be an Equal Opportunity/Affirmative Action-Employer, making decisions without regard to race, color, religion, gender, gender identity or expression, sexual orientation, national origin, genetics, disability status, age, marital status, protected veteran status or any other protected class. Our global non-discrimination policy covers these protected classes in every market in which we do business worldwide. Learn more about how we are driving diversity and inclusion in everything we do by visiting the NIQ News Center: https://nielseniq.com/global/en/news-center/diversity-inclusion I'm interested I'm interested Privacy Policy

Digital Health Associates Pvt. Ltd. is looking for an AI/ML & Backend Developer Intern excited about building intelligent and interactive AI systems. You'll work on real-world use cases involving agentic AI, LLMs, and retrieval-augmented generation (RAG) using tools like LangChain, LangGraph, and FastAPI. Responsibilities: Build and experiment with agentic AI workflows using LangChain and LangGraph Integrate open-source LLMs via tools like Ollama, LM Studio, etc. Create backend services and APIs using FastAPI Work with embedding models and vector search for intelligent retrieval tasks Collaborate with team members to prototype and deploy AI-driven features Requirements: Proficiency in Python and backend development with FastAPI Familiarity with LangChain, LangGraph, and agent-based AI concepts Experience using open-source LLMs (e.g., Mistral, LLaMA, Zephyr) locally or through inference tools like Ollama/LM Studio Basic understanding of RAG (Retrieval-Augmented Generation) and vector databases Comfortable with Git, Docker, and basic API integrations Good to Have: Exposure to prompt engineering and LLM fine-tuning Knowledge of tools like Weaviate, Qdrant, ChromaDB Familiarity with DevOps or cloud deployment (AWS/GCP) Job Type: Internship Contract length: 3 months Pay: ₹15,000.00 - ₹20,000.00 per month Benefits: Paid time off Location Type: Remote Schedule: Day shift Fixed shift Work Location: Remote Speak with the employer +91 9911100774

At Lilly, we unite caring with discovery to make life better for people around the world. We are a global healthcare leader headquartered in Indianapolis, Indiana. Our employees around the world work to discover and bring life-changing medicines to those who need them, improve the understanding and management of disease, and give back to our communities through philanthropy and volunteerism. We give our best effort to our work, and we put people first. We’re looking for people who are determined to make life better for people around the world. Lilly’s Purpose: At Lilly, we unite caring with discovery to make life better for people around the world. We are a global healthcare leader headquartered in Indianapolis, Indiana. Our 42,000+ employees across the globe work to discover and bring life-changing medicines to those who need them, improve the understanding and management of disease, and give back to our communities through philanthropy and volunteerism. We give our best effort to our work and put people first. Come build advanced software capabilities to accelerate our digital transformation and support Lilly’s evolution to be the leader in Pharma-tech! The Role: The Software Product Engineering (SPE) organization is actively looking for a Senior Quality Engineer with strong hands-on experience in AI platform testing, chatbot testing, AI model validation, agents testing, AI test automation, and API testing . This is a highly specialized role focused on validating complex AI and ML systems and ensuring scalable, safe, and effective deployment of AI-based solutions. UI automation experience using tools like Selenium , Cypress , or Playwright is desirable as a secondary skill . What You’ll Be Doing: You will drive quality engineering initiatives specifically focused on AI-powered platforms and solutions , including LLMs, chatbots, AI agents, and intelligent workflows. You’ll build robust test strategies and frameworks to validate data pipelines, model inference accuracy, prompt engineering, hallucination control, API contracts, and performance under real-world conditions. This role requires strong analytical and problem-solving skills, a deep understanding of AI systems testing, and the ability to collaborate across multidisciplinary teams such as SWE, SRE, ML Engineering, and Product. Key Responsibilities: AI Platform & Model Testing (Primary Focus): Validate the behaviour and performance of AI/ML models, including LLMs , RAG pipelines , chatbots , and autonomous agents . Design and execute prompt evaluation , response accuracy , toxicity detection , and hallucination control test scenarios. Implement and enhance automated AI testing frameworks tailored to model versioning, retraining, and feedback loops. Ensure quality in human-in-the-loop (HITL) and continuous learning pipelines. API Testing: Conduct thorough API validation using Postman , REST Assured , or GraphQL , with a focus on AI service endpoints, inference APIs, and orchestrators. Build robust integration test suites to ensure seamless functionality between APIs and underlying AI systems. AI Test Automation: Build test harnesses to validate AI features through synthetic data, mock services, and model stubs. Integrate test suites into CI/CD pipelines to ensure continuous validation of AI behaviors. UI and Functional Test Automation (Secondary Focus): Support end-to-end automation of AI-powered applications using tools such as Selenium , Cypress , Playwright , and WebdriverIO . Automate critical user journeys involving AI-enabled decisions and interactions. Collaboration & Test Strategy: Work closely with ML Engineers , SREs , and Product Managers to translate model design into testable components. Monitor AI behavior in production using observability tools and adjust quality strategies based on live insights. Drive discussions on fairness , bias , explainability , and model drift . Agile & DevOps Integration: Participate in Agile ceremonies and actively contribute to sprint planning, test case reviews, and retrospectives. Collaborate with DevOps teams to embed AI testing into CI/CD workflows using tools like GitHub , Jenkins , and Azure DevOps . Required Technical Skills & Qualifications: Bachelor’s or Master’s degree in Computer Science, Engineering, AI/ML, or a related field 6+ years of experience in Quality Engineering with at least 2 years in AI platform testing or model validation Hands-on experience in AI model testing, chatbot testing, prompt tuning , or agent workflows Proficiency in AI test automation and API testing tools (Postman, REST Assured, GraphQL) Working knowledge of Python , JavaScript , or TypeScript Experience integrating tests into CI/CD pipelines using GitHub , Jenkins , or Azure DevOps Knowledge of OpenAI , Bedrock , Anthropic , LangChain , RAG , and vector stores Understanding of LLM evaluation techniques , including metrics like BLEU , ROUGE , Toxicity Score , and RAGAs Preferred Qualifications: Experience testing AI applications hosted in multi-geographical and cloud-native environments (e.g., AWS, GCP, Azure) Exposure to AI observability platforms such as Weights & Biases , Arize AI , or WhyLabs Understanding of prompt engineering , embedding quality , and tokenization behaviour Familiarity with security , performance , or accessibility testing Experience with AI governance frameworks and regulatory compliance (e.g., FDA, HIPAA in AI contexts) Lilly is dedicated to helping individuals with disabilities to actively engage in the workforce, ensuring equal opportunities when vying for positions. If you require accommodation to submit a resume for a position at Lilly, please complete the accommodation request form (https://careers.lilly.com/us/en/workplace-accommodation) for further assistance. Please note this is for individuals to request an accommodation as part of the application process and any other correspondence will not receive a response. Lilly does not discriminate on the basis of age, race, color, religion, gender, sexual orientation, gender identity, gender expression, national origin, protected veteran status, disability or any other legally protected status. #WeAreLilly