1137 Mlflow Jobs - Page 7

Optum is a global organization that delivers care, aided by technology to help millions of people live healthier lives. The work you do with our team will directly improve health outcomes by connecting people with the care, pharmacy benefits, data and resources they need to feel their best. Here, you will find a culture guided by inclusion, talented peers, comprehensive benefits and career development opportunities. Come make an impact on the communities we serve as you help us advance health optimization on a global scale. Join us to start Caring. Connecting. Growing together. At Optum AI, we leverage data and resources to make a significant impact on the healthcare system. Our solutions have the potential to improve healthcare for everyone. We work on cutting-edge projects involving ML, NLP, and LLM techniques, continuously developing and improving generative AI methods for structured and unstructured healthcare data. Our team collaborates with world-class experts and top universities to develop innovative AI/ML solutions, often leading to patents and published papers. Primary Responsibilities: Develop and implement AI and machine learning strategies for several healthcare domains Collaborate with cross-functional teams to identify and prioritize AI and machine learning initiatives Develop and run pipelines for data ingress and model output egress Develop and run scripts for ML model inference Design, implement, and maintain CI/CD pipelines for MLOps and DevOps functions Identify technical problems and develop software updates and fixes Develop scripts or tools to automate repetitive tasks Automate the provisioning and configuration of infrastructure resources Provide guidance on the best use of specific tools or technologies to achieve desired results Create documentation for infrastructure design and deployment procedures Utilize AI/ML frameworks and tools such as MLFlow, TensorFlow, PyTorch, Keras, Scikit-learn, etc. Lead and manage AI/ML teams and projects from ideation to delivery and evaluation Apply expertise in various AI/ML techniques, including deep learning, NLP, computer vision, recommender systems, reinforcement learning, and large language models Communicate complex AI/ML concepts and results to technical and non-technical audiences effectively Comply with the terms and conditions of the employment contract, company policies and procedures, and any and all directives (such as, but not limited to, transfer and/or re-assignment to different work locations, change in teams and/or work shifts, policies in regards to flexibility of work benefits and/or work environment, alternative work arrangements, and other decisions that may arise due to the changing business environment). The Company may adopt, vary or rescind these policies and directives in its absolute discretion and without any limitation (implied or otherwise) on its ability to do so Required Qualifications: Bachelor's degree or higher in computer science engineering with a focus on language processing 8+ years of experience in Software Engineering, Data Science, or Analytics with 4+ years of experience in AI/ML engineering or related fields Hands-on experience in AI and drive the development of innovative AI and machine learning solutions Experience in developing solutions in the NLP space and relevant projects Experience with cloud platforms and services, such as AWS, Azure, GCP, etc. Experience with DevOps and CI/CD tools and practices, such as Git, Jenkins, Docker, Kubernetes, etc. Experience with Azure development environments Experience with using and deploying LLMs Knowledge of NLP literature, thrust areas, conference venues, and code repositories Familiarity with both open-source and OpenAI LLMs and RAG architecture Familiarity with UI tools like Streamlit, Flask, FAST APIs, Rest APIs, Docker containers Understanding of common NLP tasks such as text classification, entity recognition, entity extraction, and question answering Proficiency in multiple machine learning and AI techniques such as supervised, unsupervised, reinforcement learning, deep learning, and NLP Proficient in Python and one of PySpark. Familiarity with python tools for data processing Proficiency in libraries such as Hugging Face and OpenAI API Proficiency in Python, R, or other programming languages for data analysis and AI/ML development Proven hands-on skills with repository management and GPU use, and the ability to rapidly set up NLP pipelines for testing new ideas Proven ability to develop and deploy data pipelines, machine learning models, or applications on cloud platforms (Azure, Databricks, AzureML) Proven excellent analytical and problem-solving skills, including the ability to disaggregate issues, identify root causes, and recommend solutions At UnitedHealth Group, our mission is to help people live healthier lives and make the health system work better for everyone. We believe everyone–of every race, gender, sexuality, age, location and income–deserves the opportunity to live their healthiest life. Today, however, there are still far too many barriers to good health which are disproportionately experienced by people of color, historically marginalized groups and those with lower incomes. We are committed to mitigating our impact on the environment and enabling and delivering equitable care that addresses health disparities and improves health outcomes - an enterprise priority reflected in our mission.

Optum is a global organization that delivers care, aided by technology to help millions of people live healthier lives. The work you do with our team will directly improve health outcomes by connecting people with the care, pharmacy benefits, data and resources they need to feel their best. Here, you will find a culture guided by inclusion, talented peers, comprehensive benefits and career development opportunities. Come make an impact on the communities we serve as you help us advance health optimization on a global scale. Join us to start Caring. Connecting. Growing together. At Optum AI, we leverage data and resources to make a significant impact on the healthcare system. Our solutions have the potential to improve healthcare for everyone. We work on cutting-edge projects involving ML, NLP, and LLM techniques, continuously developing and improving generative AI methods for structured and unstructured healthcare data. Our team collaborates with world-class experts and top universities to develop innovative AI/ML solutions, often leading to patents and published papers. Primary Responsibilities: Develop and run pipelines for data ingress and model output egress Develop and run scripts for ML model inference Design, implement, and maintain CI/CD pipelines for MLOps and DevOps functions Identify technical problems and develop software updates and fixes Develop scripts or tools to automate repetitive tasks Automate the provisioning and configuration of infrastructure resources Provide guidance on the best use of specific tools or technologies to achieve desired results Create documentation for infrastructure design and deployment procedures Utilize AI/ML frameworks and tools such as MLFlow, TensorFlow, PyTorch, Keras, Scikit-learn, etc. Lead and manage AI/ML teams and projects from ideation to delivery and evaluation Apply expertise in various AI/ML techniques, including deep learning, NLP, computer vision, recommender systems, reinforcement learning, and large language models Communicate complex AI/ML concepts and results to technical and non-technical audiences effectively Comply with the terms and conditions of the employment contract, company policies and procedures, and any and all directives (such as, but not limited to, transfer and/or re-assignment to different work locations, change in teams and/or work shifts, policies in regards to flexibility of work benefits and/or work environment, alternative work arrangements, and other decisions that may arise due to the changing business environment). The Company may adopt, vary or rescind these policies and directives in its absolute discretion and without any limitation (implied or otherwise) on its ability to do so Required Qualifications: Bachelor's degree or higher in computer science engineering with a focus on language processing 6+ years of experience in AI/ML roles Experience with Azure development environments Experience with using and deploying LLMs Experience in developing solutions in the NLP space and relevant projects Proficiency in multiple machine learning and AI techniques such as supervised, unsupervised, reinforcement learning, deep learning, and NLP Proficient in Python and one of PySpark or Scala Familiarity with python tools for data processing Proficiency in libraries such as Hugging Face and OpenAI API Proficiency in Python, R, or other programming languages for data analysis and AI/ML development Familiarity with both open-source and OpenAI LLMs and RAG architecture Familiarity with UI tools like Streamlit, Flask, FAST APIs, Rest APIs, Docker containers Understanding of common NLP tasks such as text classification, entity recognition, entity extraction, and question answering Knowledge of NLP literature, thrust areas, conference venues, and code repositories Hands-on skills with repository management and GPU use, and the ability to rapidly set up NLP pipelines for testing new ideas Proven excellent analytical and problem-solving skills, including the ability to disaggregate issues, identify root causes, and recommend solutions Ability to develop and deploy data pipelines, machine learning models, or applications on cloud platforms (Azure, Databricks, AzureML) DevOps Skills: Experience building and maintaining CI/CD pipelines Experience with DevOps tools (GitHub, GitHub Actions, Azure devops, Kubernetes, etc) Experience with data-oriented workflow orchestration frameworks (Airflow, kafka, etc) Security and vulnerability management Familiarity with traditional software monitoring, scaling, and quality management (QMS) Preferred Qualifications: Experience deploying and maintaining ML models in production Experience with model observability tools for insights into the behavior, performance, and health of deployed ML models (tracking, alerting, compliance monitoring, etc) MLOps skills Familiarity with model versioning tools (MLFlow, etc) Familiarity with data versioning tools (Delta Lake, DVC, LakeFS, etc) At UnitedHealth Group, our mission is to help people live healthier lives and make the health system work better for everyone. We believe everyone-of every race, gender, sexuality, age, location and income-deserves the opportunity to live their healthiest life. Today, however, there are still far too many barriers to good health which are disproportionately experienced by people of color, historically marginalized groups and those with lower incomes. We are committed to mitigating our impact on the environment and enabling and delivering equitable care that addresses health disparities and improves health outcomes - an enterprise priority reflected in our mission.

Responsibilities: Build and optimize RAG (Retrieval-Augmented Generation) and Agentic AI workflows using LangChain, vector databases (Pinecone, FAISS, ChromaDB), and embedding models. Implement LLM fine-tuning, prompt chaining, and response ranking to enhance generative AI performance. Develop and evaluate retrieval mechanisms using semantic search and vector similarity techniques. Benchmark model performance using BLEU, ROUGE, METEOR, BERTScore, and other LLM evaluation metrics. Deploy AI models in production environments (AWS, GCP, Azure) with MLOps best practices for monitoring and retraining. Stay updated on the latest advancements in LLMs, transformers, and multi-agent AI architectures, applying new techniques to improve AI-driven applications. Requirements: Hands-on experience in Generative AI, RAG, and Agentic AI workflows, with expertise in LangChain, embedding models, and vector databases (Pinecone, FAISS, ChromaDB). Strong Python skills with experience in Hugging Face, PyTorch, TensorFlow, and scikit-learn for LLM fine-tuning and prompt engineering. Proficiency in benchmarking LLMs using BLEU, ROUGE, METEOR, and BERTScore, ensuring model quality and optimization. Experience in cloud-based deployments (AWS, GCP, Azure) and MLOps tools (MLflow, Weights & Biases, KubeFlow) for monitoring and retraining. Familiarity with containerized deployments (Docker, Kubernetes) and distributed computing (Ray, Spark) for scalable AI workloads. Strong problem-solving skills, with the ability to optimize LLM pipelines for latency, efficiency, and real-world applications.

Key Responsibilities Business Understanding & Solutioning Engage with clients/stakeholders to define analytics roadmaps. Translate business problems into ML, DL, or GenAI-driven analytical solutions. Participate in pre-sales activities, including creating pitch decks, framing solutions, and presenting to clients. Modeling & AI Development Develop models for Prediction, Forecast, Segmentation, Churn, CLV, Recommendation Systems. Build Generative AI solutions using LLMs, Transformers, Autoencoders. Implement scalable AI/ML pipelines with MLOps tools (MLflow, Docker, CI/CD). Team Leadership & Collaboration Lead and mentor 5–10+ data scientists. Work with engineering, product, and client teams to integrate AI in workflows. Knowledge Sharing & Mindset Promote a learning culture; share knowledge across the team. Coach junior ML members and foster collaboration.

About the Role We are seeking a passionate and skilled AI Engineer with 2 to 5 years of hands-on experience to join our team. You will be responsible for designing, developing, and deploying machine learning and AI-based solutions that drive value across our products and services. If you have a strong foundation in AI/ML techniques and a desire to build impactful systems at scale, we’d love to connect. Key Responsibilities Design, build, and deploy AI/ML models to solve business problems. Work with data scientists, engineers, and product managers to translate requirements into scalable AI solutions. Preprocess and analyze large datasets to extract meaningful insights. Optimize and fine-tune models for performance, accuracy, and scalability. Stay up to date with the latest AI/ML research and incorporate best practices into development. Collaborate in code reviews, model validation, and documentation efforts. Required Skills & Qualifications Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, Machine Learning, or related field. 2–5 years of experience in building and deploying ML/AI models. Strong programming skills in Python (TensorFlow, PyTorch, scikit-learn, etc.). Proficiency in data handling libraries like Pandas and NumPy. Experience with NLP, Computer Vision, or Predictive Analytics is a plus. Familiarity with ML lifecycle tools such as MLflow, Airflow, or similar. Experience with cloud platforms (AWS/GCP/Azure) and model deployment practices. Understanding of software engineering best practices including version control, CI/CD, and testing. Good to have Contributions to open-source AI/ML projects or publications in the field. Experience with databases including vector databases (e.g., Qdrant, Chroma, Pinecone) and traditional databases (e.g., PostgreSQL, MongoDB) Working with RESTful APIs for backend service integrations.

Job Summary We are looking for an experienced Azure Databricks Developer to design, develop, and manage big data solutions using Azure services, with a strong focus on Databricks , Spark , and ETL pipelines . The ideal candidate will have a solid understanding of data engineering, Azure cloud components, and real-time/batch data processing. Key Responsibilities Design and build scalable and robust data pipelines using Azure Databricks (Spark). Develop ETL/ELT processes for ingesting, transforming, and loading data from various sources. Integrate data solutions with Azure Data Lake, Azure Data Factory, and SQL Databases. Optimize Spark jobs for performance and cost-efficiency. Collaborate with data architects, analysts, and business stakeholders to deliver data solutions. Implement data quality checks, validations, and unit testing. Ensure best practices in CI/CD, data security, and governance. Must-Have Skills Strong hands-on experience with Azure Databricks and Apache Spark (PySpark/Scala). Proficiency in Azure Data Factory, Azure Data Lake, and Azure Synapse (optional). Solid understanding of SQL, Delta Lake, and data warehousing concepts. Experience building automated data pipelines and working with large datasets. Good understanding of DevOps, version control (e.g., Git), and CI/CD pipelines. Strong problem-solving and debugging skills. Nice-to-Have Experience with Azure Synapse Analytics, Power BI, or Kafka/Event Hub integration. Familiarity with DataBricks REST APIs, MLFlow, or Databricks Jobs orchestration. Knowledge of data modeling, data governance, and metadata management. Qualifications Bachelor’s or Master’s degree in Computer Science, Information Systems, or related field. Azure certifications (e.g., DP-203, Azure Data Engineer Associate) are a plus. Skills: python,delta lake,apache spark (pyspark/scala),pyspark,ci/cd,azure data lake,azure,azure data factory,etl/elt processes,data governance,azure databricks,data modeling,git,databricks,metadata management,architect,sql

Job Summary We are looking for an experienced Azure Databricks Developer to design, develop, and manage big data solutions using Azure services, with a strong focus on Databricks , Spark , and ETL pipelines . The ideal candidate will have a solid understanding of data engineering, Azure cloud components, and real-time/batch data processing. Key Responsibilities Design and build scalable and robust data pipelines using Azure Databricks (Spark). Develop ETL/ELT processes for ingesting, transforming, and loading data from various sources. Integrate data solutions with Azure Data Lake, Azure Data Factory, and SQL Databases. Optimize Spark jobs for performance and cost-efficiency. Collaborate with data architects, analysts, and business stakeholders to deliver data solutions. Implement data quality checks, validations, and unit testing. Ensure best practices in CI/CD, data security, and governance. Must-Have Skills Strong hands-on experience with Azure Databricks and Apache Spark (PySpark/Scala). Proficiency in Azure Data Factory, Azure Data Lake, and Azure Synapse (optional). Solid understanding of SQL, Delta Lake, and data warehousing concepts. Experience building automated data pipelines and working with large datasets. Good understanding of DevOps, version control (e.g., Git), and CI/CD pipelines. Strong problem-solving and debugging skills. Nice-to-Have Experience with Azure Synapse Analytics, Power BI, or Kafka/Event Hub integration. Familiarity with DataBricks REST APIs, MLFlow, or Databricks Jobs orchestration. Knowledge of data modeling, data governance, and metadata management. Qualifications Bachelor’s or Master’s degree in Computer Science, Information Systems, or related field. Azure certifications (e.g., DP-203, Azure Data Engineer Associate) are a plus. Skills: python,delta lake,apache spark (pyspark/scala),pyspark,ci/cd,azure data lake,azure,azure data factory,etl/elt processes,data governance,azure databricks,data modeling,git,databricks,metadata management,architect,sql

Job Summary We are looking for an experienced Azure Databricks Developer to design, develop, and manage big data solutions using Azure services, with a strong focus on Databricks , Spark , and ETL pipelines . The ideal candidate will have a solid understanding of data engineering, Azure cloud components, and real-time/batch data processing. Key Responsibilities Design and build scalable and robust data pipelines using Azure Databricks (Spark). Develop ETL/ELT processes for ingesting, transforming, and loading data from various sources. Integrate data solutions with Azure Data Lake, Azure Data Factory, and SQL Databases. Optimize Spark jobs for performance and cost-efficiency. Collaborate with data architects, analysts, and business stakeholders to deliver data solutions. Implement data quality checks, validations, and unit testing. Ensure best practices in CI/CD, data security, and governance. Must-Have Skills Strong hands-on experience with Azure Databricks and Apache Spark (PySpark/Scala). Proficiency in Azure Data Factory, Azure Data Lake, and Azure Synapse (optional). Solid understanding of SQL, Delta Lake, and data warehousing concepts. Experience building automated data pipelines and working with large datasets. Good understanding of DevOps, version control (e.g., Git), and CI/CD pipelines. Strong problem-solving and debugging skills. Nice-to-Have Experience with Azure Synapse Analytics, Power BI, or Kafka/Event Hub integration. Familiarity with DataBricks REST APIs, MLFlow, or Databricks Jobs orchestration. Knowledge of data modeling, data governance, and metadata management. Qualifications Bachelor’s or Master’s degree in Computer Science, Information Systems, or related field. Azure certifications (e.g., DP-203, Azure Data Engineer Associate) are a plus. Skills: python,delta lake,apache spark (pyspark/scala),pyspark,ci/cd,azure data lake,azure,azure data factory,etl/elt processes,data governance,azure databricks,data modeling,git,databricks,metadata management,architect,sql

Who are we: Turbostart is not just a startup fund and accelerator — we are a catalyst for builders and a powerhouse of innovation. Our mission is to propel early-stage startups into the future by providing unparalleled support in technology, marketing, strategy, and beyond. We're in the business of building tomorrow's leaders — today. After 5 years and 5 funds, we have supported over 50 startups spanning sectors, stages, and geographies — and this is just the beginning! Turbostart spans India, the Middle East, the US, and Singapore — giving you the opportunity to gain exposure and see the impact of your work ripple across regions. Turbostart has also launched 5 Centers of Excellence across Tech, Marketing, Sales, UI/UX, and Investment Banking to support the growth of our startup network. Know more about us: https://turbostart.co Turbostart Technology Development Centre (T2C) is a leading Center of Excellence within the Turbostart ecosystem. T2C plays a pivotal role by providing cutting-edge technology solutions and expertise to our portfolio companies and by building new-age software products from the ground up. Know more about us: https://tsquaredc.com What we are looking for: Role: AI Engineer We are looking for a dynamic and skilled AI Engineer with 2+ years of experience in designing, developing, and deploying machine learning solutions. You’ll work across data-rich problem statements, collaborating closely with product and engineering teams to build intelligent systems that scale. Location: Kolkata, West Bengal, India Experience Required: 2–4 years of hands-on experience in AI/ML engineering or applied data science. What you’ll do: Design and implement cutting-edge machine learning and deep learning models for various use cases, with a strong focus on conversational AI (voice agents, chatbots), natural language understanding and generation, and generative media (images, video). Work with large datasets to preprocess, clean, and extract insights, including diverse modalities such as audio, visual, and textual data for advanced AI applications. Build and maintain robust data pipelines and model-serving frameworks, ensuring scalable and real-time deployment for conversational agents and high-throughput generative services. Collaborate with product managers and developers to integrate sophisticated ML models into scalable systems, such as voice platforms, intelligent chatbot frameworks, and content creation pipelines. Optimize model performance through hyperparameter tuning and continuous retraining, applying domain-specific evaluation metrics for conversational fluency, image realism, video quality, and natural language understanding. Conduct in-depth research on new AI technologies and assess their feasibility for implementation, with a particular emphasis on state-of-the-art Large Language Models (LLMs), multimodal AI, speech synthesis, generative adversarial networks (GANs), and diffusion models. Ensure model explainability, accuracy, and fairness in deployment environments, paying close attention to potential biases in generative content, conversational interactions, and ethical AI principles. Write clean, reusable code and maintain proper documentation of experiments and model versions, especially for iterative development in generative AI and complex conversational flows Our ideal candidate: Bachelor’s degree in Computer Science, Engineering, or a related field (or equivalent practical experience). Proficiency in Python and ML frameworks such as TensorFlow, PyTorch, and scikit-learn. Extensive experience with model development, training, validation, and deployment in production environments. Familiarity with REST APIs and integrating ML models with web services or applications. Strong understanding and hands-on experience with generative AI models (GANs, VAEs, Diffusion Models). Experience with Large Language Models (LLMs), including fine-tuning, prompt engineering, and Retrieval-Augmented Generation (RAG). Proficiency in Natural Language Processing (NLP), including NLU, NLG, intent recognition, entity extraction, and dialogue management. Hands-on experience with speech technologies such as Automatic Speech Recognition (ASR) and Text-to-Speech (TTS). Knowledge of computer vision techniques like image/video processing, object detection, and segmentation, especially for generative media. Familiarity with tools and APIs for conversational and generative AI (e.g., Vapi, Retell, Ultravox, 11 Labs). Experience working with LLM/multimodal APIs such as OpenAI (GPT, DALL-E, Whisper), Claude API, and Gemini API. Exposure to video generation tools like Veo2 or similar platforms. Experience using model tracking and visualization tools like Jupyter, MLflow, or TensorBoard. Exposure to cloud platforms (AWS, GCP, or Azure) and containerization tools like Docker. Understanding of key AI performance metrics including F1-score, AUC-ROC, IS, FID, BLEU, ROUGE, WER, and others relevant to different model types. Strong problem-solving and communication skills. Ability to work independently and collaboratively in a fast-paced, agile environment. Why join us Work on cutting-edge projects with startups across multiple industries. Be at the forefront of building next-gen tech products in emerging sectors. Work in a high-autonomy environment that values speed, experimentation, and innovation. Collaborate with cross-functional experts across engineering, design, product, and strategy.

Department: Data Science / AI Job Type: Full-time Job Summary: We are looking for a skilled and results-driven Machine Learning Engineer to join our team. The ideal candidate will be responsible for designing, building, and deploying scalable machine learning models and pipelines that solve real-world problems and drive business value. Key Responsibilities: · Design and implement machine learning models for classification, regression, recommendation, NLP, or computer vision tasks. · Build and deploy ML pipelines using tools like TensorFlow, PyTorch, Scikit-learn, or MLflow. · Collaborate with data scientists, data engineers, and product teams to integrate models into production systems. · Analyze large, complex datasets to derive actionable insights and drive model development. · Conduct experiments, tune hyperparameters, and evaluate model performance using industry-standard metrics. · Ensure robustness, fairness, and scalability of machine learning systems. · Monitor and maintain deployed models, including retraining and updating as needed. Required Skills & Qualifications: · Bachelor's or Master’s degree in Computer Science, Artificial Intelligence, Data Science, or related field. · 3+ years of experience in machine learning, data science, or applied AI roles. · Proficiency in Python and ML libraries (Scikit-learn, TensorFlow, PyTorch, XGBoost, etc.). · Experience with data manipulation tools (Pandas, NumPy) and SQL. · Hands-on experience in deploying ML models into production (using REST APIs, Docker, Kubernetes, etc.). · Solid understanding of ML algorithms, model evaluation, and overfitting/underfitting concepts. · Familiarity with cloud platforms (AWS, GCP, Azure) is a plus. Preferred Qualifications: · Experience with NLP (e.g., BERT, GPT), computer vision (e.g., CNNs, OpenCV), or time-series forecasting. · Exposure to MLOps tools and practices (e.g., MLflow, DVC, Kubeflow). · Understanding of data engineering practices and pipeline automation.

Title: Senior Data Scientist Years of Experience : 8+ years Location : Onsite (The selected candidate is required to relocate to Kovilpatti, Tamil Nadu, for the initial three-month project training session . Post training, the candidate will be relocated to one of our onsite locations: Chennai, Hyderabad, or Pune , based on project allocation.) Job Description The Senior Data Scientist will lead the development and implementation of advanced analytics and AI/ML models to solve complex business problems. This role requires deep statistical expertise, hands-on model building experience, and the ability to translate raw data into strategic insights. The candidate will collaborate with business stakeholders, data engineers, and AI engineers to deploy production-grade models that drive innovation and value. Key responsibilities · Lead end-to-end model lifecycle: data exploration, feature engineering, model training, validation, deployment, and monitoring · Develop predictive models, recommendation systems, anomaly detection, NLP models, and generative AI applications · Conduct statistical analysis and hypothesis testing for business experimentation · Optimize model performance using hyperparameter tuning, ensemble methods, and explainable AI (XAI) · Collaborate with data engineering teams to improve data pipelines and quality · Document methodologies, build reusable ML components, and publish technical artifacts · Mentor junior data scientists and contribute to CoE-wide model governance Technical Skills ML Frameworks: Scikit-learn, TensorFlow, PyTorch, XGBoost Statistical tools: Python (NumPy, Pandas, SciPy), R, SAS NLP & LLMs: Hugging Face Transformers, GPT APIs, BERT, LangChain Model deployment: MLflow, Docker, Azure ML, AWS Sagemaker Data visualization: Power BI, Tableau, Plotly, Seaborn SQL and NoSQL (CosmosDB, MongoDB) Git, CI/CD tools, and model monitoring platforms Qualification Master’s in Data Science, Statistics, Mathematics, or Computer Science Microsoft Certified: Azure Data Scientist Associate or equivalent Proven success in delivering production-ready ML models with measurable business impact Publications or patents in AI/ML will be considered a strong advantage. Job Type: Full-time Pay: Up to ₹80,000.00 per month Ability to commute/relocate: Kovilpatti, Tamil Nadu: Reliably commute or willing to relocate with an employer-provided relocation package (Required) Application Question(s): Expected salary in annual (INR)? Experience: Data Scientist: 8 years (Required) License/Certification: Azure Data Scientist Associate (Required) Work Location: In person

Title: Senior Data Scientist Years of Experience : 8+ years *Location: The selected candidate is required to work onsite at our Chennai location for the initial six-month project training and execution period. After the six months , the candidate will be offered remote opportunities.* Job Description The Senior Data Scientist will lead the development and implementation of advanced analytics and AI/ML models to solve complex business problems. This role requires deep statistical expertise, hands-on model building experience, and the ability to translate raw data into strategic insights. The candidate will collaborate with business stakeholders, data engineers, and AI engineers to deploy production-grade models that drive innovation and value. Key responsibilities Lead end-to-end model lifecycle: data exploration, feature engineering, model training, validation, deployment, and monitoring Develop predictive models, recommendation systems, anomaly detection, NLP models, and generative AI applications Conduct statistical analysis and hypothesis testing for business experimentation Optimize model performance using hyperparameter tuning, ensemble methods, and explainable AI (XAI) Collaborate with data engineering teams to improve data pipelines and quality Document methodologies, build reusable ML components, and publish technical artifacts Mentor junior data scientists and contribute to CoE-wide model governance Technical Skills ML Frameworks: Scikit-learn, TensorFlow, PyTorch, XGBoost Statistical tools: Python (NumPy, Pandas, SciPy), R, SAS NLP & LLMs: Hugging Face Transformers, GPT APIs, BERT, LangChain Model deployment: MLflow, Docker, Azure ML, AWS Sagemaker Data visualization: Power BI, Tableau, Plotly, Seaborn SQL and NoSQL (CosmosDB, MongoDB) Git, CI/CD tools, and model monitoring platforms Qualification Master’s in Data Science, Statistics, Mathematics, or Computer Science Microsoft Certified: Azure Data Scientist Associate or equivalent Proven success in delivering production-ready ML models with measurable business impact Publications or patents in AI/ML will be considered a strong advantage. Job Type: Full-time Pay: Up to ₹80,000.00 per month Ability to commute/relocate: Chennai, Tamil Nadu: Reliably commute or planning to relocate before starting work (Required) Application Question(s): Expected salary in annual (INR)? Experience: Data Scientist: 8 years (Required) License/Certification: Azure Data Scientist Associate (Required) Work Location: In person

This role is for one of our clients Industry: Technology, Information and Media Seniority level: Mid-Senior level Min Experience: 8 years Location: Mumbai JobType: full-time Overview: We are on the hunt for a forward-thinking Head of Product to lead our AI/ML and enterprise analytics initiatives. This is a high-ownership role for a strategic product leader with deep technical fluency and a passion for building AI-first solutions that transform how businesses leverage data. You’ll drive the vision, roadmap, and execution of intelligent analytics products that harness cutting-edge technologies—from large language models and generative AI to real-time data intelligence. If you thrive at the intersection of innovation, execution, and impact, this is your platform to lead. What You’ll Own 🔍 Vision & Strategy Define and evolve the end-to-end product strategy for AI/ML-powered tools in analytics, insights, and decision intelligence. Translate customer needs and market signals into differentiated product opportunities. Stay ahead of the curve by integrating frontier tech—LLMs, autonomous agents, vector search, etc.—into a cohesive product vision. 🚀 Product Execution & Innovation Lead the ideation, scoping, and launch of ML-driven features that power predictive analytics, NLP pipelines, real-time dashboards, and embedded intelligence. Partner closely with engineering, design, and data science to ship scalable, production-ready solutions. Champion data pipeline optimization, experimentation frameworks, and robust MLOps practices to support model lifecycle management. 📊 Customer & Market Impact Conduct deep discovery with enterprise clients to co-design high-ROI solutions. Ensure user-centricity through iterative feedback loops, proof-of-concepts, and product analytics. Own adoption metrics, customer retention, and monetization strategies for the AI product suite. 🤝 Leadership & Collaboration Mentor a cross-functional product team and align them with ambitious yet achievable goals. Build internal alignment across GTM, Engineering, and Customer Success on product direction. Act as a thought leader both internally and externally—driving industry positioning, events, and advisory roles. What You Bring 💡 Technical Expertise Master’s or PhD in Computer Science, Data Science, Machine Learning, or a related field. 8–12 years of experience in AI/ML, advanced analytics, or enterprise-grade data science platforms. Strong grasp of ML/NLP models, GenAI/LLM stacks (e.g., LangChain, Hugging Face), and experience working with scalable architectures (e.g., vector DBs, streaming data, cloud-native ML). 🧠 Product Acumen 5+ years in product management, including 2+ years in a leadership or head-of-product capacity. Proven ability to ship AI-first B2B or enterprise products—especially in the BI, analytics, or automation spaces. Experience managing the full product lifecycle: roadmap creation, launch, iteration, scale. 📈 Business & Communication Strength Strong product storytelling and executive presence—able to align stakeholders around a data-driven narrative. Fluency in translating complex technical outputs into user value and commercial impact. Past involvement in GTM strategies, pricing models, or product-led growth (PLG) initiatives. Bonus Points For Experience with MLOps platforms like MLflow, Vertex AI, or Databricks. Prior success in a growth-stage startup or enterprise SaaS company. Familiarity with global data privacy and governance frameworks (GDPR, HIPAA, etc.). Background in working with enterprise clients in verticals like fintech, healthcare, or manufacturing.

Job Title: AI Infrastructure Engineer Experience: 8+ Years Location: Onsite ( Note: The selected candidate is required to relocate to Kovilpatti, Tamil Nadu for the initial three-month project training session . Post training, the candidate will be relocated to one of our onsite locations: Chennai, Hyderabad, or Pune , based on project allocation.) Job Summary: We are looking for an experienced AI Infrastructure Engineer to architect and manage scalable, secure, and high-performance infrastructure tailored for enterprise AI and ML applications. The ideal candidate will collaborate with data scientists, DevOps, and cybersecurity teams to build reliable platforms for efficient model development, training, and deployment. Key Responsibilities: Design and implement end-to-end AI infrastructure using cloud-native tools (Azure, AWS, GCP). Build secure and scalable compute environments with GPU/TPU acceleration for model training and inference. Develop and maintain CI/CD and MLOps pipelines for the AI/ML lifecycle. Optimize large-scale AI workloads using distributed computing and hardware-aware strategies. Manage containerized deployments using orchestration platforms like Kubernetes (AKS, EKS, GKE) and Docker. Ensure system reliability, monitoring, observability, and performance tuning for real-time inference services. Implement automated rollback, logging, and infrastructure monitoring tools. Collaborate with cybersecurity teams to enforce security, data privacy, and regulatory compliance. Technical Skills: Cloud Platforms: Azure Machine Learning, AWS SageMaker, GCP Vertex AI Infrastructure-as-Code: Terraform, ARM Templates, Bicep Containerization & Orchestration: Docker, Kubernetes (AKS, EKS, GKE) MLOps Tools: MLflow, Kubeflow, Azure DevOps, GitHub Actions GPU/TPU Acceleration: CUDA, NVIDIA Triton Inference Server Security & Compliance: TLS, IAM, RBAC, Azure Key Vault Performance: Endpoint scaling, latency optimization, model caching, and resource allocation Qualifications: Bachelor's or Master's in Computer Engineering, Cloud Architecture, or a related field Microsoft Certified: Azure Solutions Architect or DevOps Engineer Expert (preferred) Proven experience deploying and managing large-scale ML pipelines and AI workloads Strong understanding of infrastructure security, networking, and cloud-based AI environments Job Type: Full-time Pay: Up to ₹80,000.00 per month Ability to commute/relocate: Tamulinadu, Tamil Nadu: Reliably commute or willing to relocate with an employer-provided relocation package (Required) Application Question(s): Expected Salary in Annual (INR) Experience: AI Infrastructure Engineer : 8 years (Required) Work Location: In person

Job Title: AI Infrastructure Engineer Experience: 8+ Years *Location: The selected candidate is required to work onsite at our Chennai location for the initial six-month project training and execution period. After the six months , the candidate will be offered remote opportunities.* Job Summary: We are looking for an experienced AI Infrastructure Engineer to architect and manage scalable, secure, and high-performance infrastructure tailored for enterprise AI and ML applications. The ideal candidate will collaborate with data scientists, DevOps, and cybersecurity teams to build reliable platforms for efficient model development, training, and deployment. Key Responsibilities: Design and implement end-to-end AI infrastructure using cloud-native tools (Azure, AWS, GCP). Build secure and scalable compute environments with GPU/TPU acceleration for model training and inference. Develop and maintain CI/CD and MLOps pipelines for the AI/ML lifecycle. Optimize large-scale AI workloads using distributed computing and hardware-aware strategies. Manage containerized deployments using orchestration platforms like Kubernetes (AKS, EKS, GKE) and Docker. Ensure system reliability, monitoring, observability, and performance tuning for real-time inference services. Implement automated rollback, logging, and infrastructure monitoring tools. Collaborate with cybersecurity teams to enforce security, data privacy, and regulatory compliance. Technical Skills: Cloud Platforms: Azure Machine Learning, AWS SageMaker, GCP Vertex AI Infrastructure-as-Code: Terraform, ARM Templates, Bicep Containerization & Orchestration: Docker, Kubernetes (AKS, EKS, GKE) MLOps Tools: MLflow, Kubeflow, Azure DevOps, GitHub Actions GPU/TPU Acceleration: CUDA, NVIDIA Triton Inference Server Security & Compliance: TLS, IAM, RBAC, Azure Key Vault Performance: Endpoint scaling, latency optimization, model caching, and resource allocation Qualifications: Bachelor's or Master's in Computer Engineering, Cloud Architecture, or a related field Microsoft Certified: Azure Solutions Architect or DevOps Engineer Expert (preferred) Proven experience deploying and managing large-scale ML pipelines and AI workloads Strong understanding of infrastructure security, networking, and cloud-based AI environments Job Type: Full-time Pay: Up to ₹80,000.00 per month Ability to commute/relocate: Chennai, Tamil Nadu: Reliably commute or planning to relocate before starting work (Required) Application Question(s): Expected Salary in Annual (INR) Experience: AI Infrastructure Engineer : 8 years (Required) Work Location: In person

Job: Product Manager Location: Bangalore/ Pune Experience: 9 Years to 15Years We are looking for a strategic and technically savvy Product Manager to lead AI-First initiatives within our AINext Platform team. This role focuses on creating scalable, impactful AI solutions by partnering closely with data scientists, engineers, and stakeholders to productize cutting-edge machine learning models and AI capabilities. As the champion of AI-first thinking, you will define and drive the roadmap for AI-powered features, infrastructure, and tools that power intelligent applications across the organization or for external customers. Responsibilities Own the product strategy for AI-first capabilities and features across the applied AI platform. Translate AI research and prototypes into production-ready products by working closely with research, data science, MLOps, and engineering teams. Define requirements for AI services , APIs, and infrastructure needed to support enterprise-scale AI use cases. Collaborate with UX, engineering, and stakeholders to prioritize AI use cases that provide real business value and measurable outcomes. Establish KPIs to measure the impact and performance of AI-driven features , and continuously optimize based on data. Evangelize an “AI-First” mindset across product and business units, helping teams adopt AI as a native capability in their products. Stay on top of the latest AI and ML trends, including foundation models, generative AI, and MLOps best practices. Drive experimentation and model validation pipelines, ensuring reliability, fairness, and explainability in deployed models. Work with responsible AI and compliance teams to ensure all AI initiatives align with ethical, privacy, and regulatory requirements . Qualifications 9+ years of product management experience, preferably in AI/ML or platform products. We have multiple roles requiring higher levels of experience. Strong understanding of machine learning, data science, and modern AI architectures , including LLMs and generative AI. Experience working with or managing AI/ML platforms, such as feature stores, model registries, MLOps pipelines, or inference services. Demonstrated ability to translate complex technical concepts into clear product requirements and business value. Excellent cross-functional communication skills, with experience working across engineering, design, research, and business teams. Familiarity with cloud platforms (AWS, GCP, Azure) and AI infrastructure tools (e.g., MLFlow, Kubeflow, Vertex AI, Databricks, etc.) Experience working in an Agile or Lean product development environment . Experience working with LLMs, embeddings, RAG pipelines, or generative AI tools (e.g., OpenAI, Hugging Face, LangChain). Prior work on B2B SaaS or internal platform products Preferred Qualifications: Technical background (Engineering, or Data Science degree preferred) with MBA preferred. What You’ll Gain: The opportunity to shape the future of AI products at an organization embracing AI-first transformation. A collaborative, forward-thinking environment with access to cutting-edge AI technologies .

Location: Onsite * Note : The selected candidate is required to relocate to Kovilpatti, Tamil Nadu for the initial three-month project training session . Post training, the candidate will be relocated to one of our onsite locations: Chennai, Hyderabad, or Pune , based on project allocation. Job Description The Senior AI Developer will be responsible for designing, building, training, and deploying advanced artificial intelligence and machine learning models to solve complex business challenges across industries. This role demands a strategic thinker and hands-on practitioner who can work at the intersection of data science, software engineering, and innovation. The candidate will contribute to scalable production-grade AI pipelines and mentor junior AI engineers within the Center of Excellence (CoE). Key responsibilities: · Design, train, and fine-tune deep learning models (NLP, CV, LLMs, GANs) for high-value applications · Architect AI model pipelines and implement scalable inference engines in cloud-native environments · Collaborate with data scientists, engineers, and solution architects to productionize ML prototypes · Evaluate and integrate pre-trained models like GPT-4o, Gemini, Claude, and fine-tune based on domain needs · Optimize algorithms for real-time performance, efficiency, and fairness · Write modular, maintainable code and perform rigorous unit testing and validation · Contribute to AI codebase management, CI/CD, and automated retraining infrastructure · Research emerging AI trends and propose innovative applications aligned with business objectives Technical Skills: · Expert in Python, PyTorch, TensorFlow, Scikit-learn, Hugging Face Transformers · LLM deployment & tuning: OpenAI (GPT), Google Gemini, Claude, Falcon, Mistral · Experience with RESTful APIs, Flask/FastAPI for AI service exposure · Proficient in Azure Machine Learning, Databricks, MLflow, Docker, Kubernetes · Hands-on experience with vector databases, prompt engineering, and retrieval-augmented generation (RAG) · Knowledge of Responsible AI frameworks (bias detection, fairness, explainability) Qualification · Master’s in Artificial Intelligence, Machine Learning, Data Science, or Computer Engineering · Certifications in AI/ML (e.g., Microsoft Azure AI Engineer, Google Professional ML Engineer) preferred · Demonstrated success in building scalable AI applications in production environments · Publications or contributions to open-source AI/ML projects are a plus. Job Type: Full-time Pay: Up to ₹80,000.00 per month Location Type: In-person Ability to commute/relocate: Kovilpatti, Tamil Nadu: Reliably commute or willing to relocate with an employer-provided relocation package (Required) Application Question(s): Expected Salary in Annual (INR)? Experience: AI Developer: 8 years (Required) Work Location: In person

Title : Senior AI Developer Experience : 8+ Years *Location: The selected candidate is required to work onsite at our Chennai location for the initial six-month project training and execution period. After the six months , the candidate will be offered remote opportunities.* Job Description The Senior AI Developer will be responsible for designing, building, training, and deploying advanced artificial intelligence and machine learning models to solve complex business challenges across industries. This role demands a strategic thinker and hands-on practitioner who can work at the intersection of data science, software engineering, and innovation. The candidate will contribute to scalable production-grade AI pipelines and mentor junior AI engineers within the Center of Excellence (CoE). Key responsibilities: Design, train, and fine-tune deep learning models (NLP, CV, LLMs, GANs) for high-value applications Architect AI model pipelines and implement scalable inference engines in cloud-native environments Collaborate with data scientists, engineers, and solution architects to productionize ML prototypes Evaluate and integrate pre-trained models like GPT-4o, Gemini, Claude, and fine-tune based on domain needs Optimize algorithms for real-time performance, efficiency, and fairness Write modular, maintainable code and perform rigorous unit testing and validation Contribute to AI codebase management, CI/CD, and automated retraining infrastructure Research emerging AI trends and propose innovative applications aligned with business objectives Technical Skills: Expert in Python, PyTorch, TensorFlow, Scikit-learn, Hugging Face Transformers LLM deployment & tuning: OpenAI (GPT), Google Gemini, Claude, Falcon, Mistral Experience with RESTful APIs, Flask/FastAPI for AI service exposure Proficient in Azure Machine Learning, Databricks, MLflow, Docker, Kubernetes Hands-on experience with vector databases, prompt engineering, and retrieval-augmented generation (RAG) Knowledge of Responsible AI frameworks (bias detection, fairness, explainability) Qualification Master’s in Artificial Intelligence, Machine Learning, Data Science, or Computer Engineering Certifications in AI/ML (e.g., Microsoft Azure AI Engineer, Google Professional ML Engineer) preferred Demonstrated success in building scalable AI applications in production environments Publications or contributions to open-source AI/ML projects are a plus. Job Type: Full-time Pay: Up to ₹80,000.00 per month Location Type: In-person Ability to commute/relocate: Chennai, Tamil Nadu: Reliably commute or planning to relocate before starting work (Required) Application Question(s): Expected Salary in Annual (INR)? Experience: AI Developer: 8 years (Required) Work Location: In person

Optum is a global organization that delivers care, aided by technology to help millions of people live healthier lives. The work you do with our team will directly improve health outcomes by connecting people with the care, pharmacy benefits, data and resources they need to feel their best. Here, you will find a culture guided by inclusion, talented peers, comprehensive benefits and career development opportunities. Come make an impact on the communities we serve as you help us advance health optimization on a global scale. Join us to start Caring. Connecting. Growing together. At Optum AI, we leverage data and resources to make a significant impact on the healthcare system. Our solutions have the potential to improve healthcare for everyone. We work on cutting-edge projects involving ML, NLP, and LLM techniques, continuously developing and improving generative AI methods for structured and unstructured healthcare data. Our team collaborates with world-class experts and top universities to develop innovative AI/ML solutions, often leading to patents and published papers. Primary Responsibilities Develop and implement AI and machine learning strategies for several healthcare domains Collaborate with cross-functional teams to identify and prioritize AI and machine learning initiatives Develop and run pipelines for data ingress and model output egress Develop and run scripts for ML model inference Design, implement, and maintain CI/CD pipelines for MLOps and DevOps functions Identify technical problems and develop software updates and fixes Develop scripts or tools to automate repetitive tasks Automate the provisioning and configuration of infrastructure resources Provide guidance on the best use of specific tools or technologies to achieve desired results Create documentation for infrastructure design and deployment procedures Utilize AI/ML frameworks and tools such as MLFlow, TensorFlow, PyTorch, Keras, Scikit-learn, etc. Lead and manage AI/ML teams and projects from ideation to delivery and evaluation Apply expertise in various AI/ML techniques, including deep learning, NLP, computer vision, recommender systems, reinforcement learning, and large language models Communicate complex AI/ML concepts and results to technical and non-technical audiences effectively Comply with the terms and conditions of the employment contract, company policies and procedures, and any and all directives (such as, but not limited to, transfer and/or re-assignment to different work locations, change in teams and/or work shifts, policies in regards to flexibility of work benefits and/or work environment, alternative work arrangements, and other decisions that may arise due to the changing business environment). The Company may adopt, vary or rescind these policies and directives in its absolute discretion and without any limitation (implied or otherwise) on its ability to do so Required Qualifications Bachelor's degree or higher in computer science engineering with a focus on language processing 8+ years of experience in Software Engineering, Data Science, or Analytics with 4+ years of experience in AI/ML engineering or related fields Hands-on experience in AI and drive the development of innovative AI and machine learning solutions Experience in developing solutions in the NLP space and relevant projects Experience with cloud platforms and services, such as AWS, Azure, GCP, etc. Experience with DevOps and CI/CD tools and practices, such as Git, Jenkins, Docker, Kubernetes, etc. Experience with Azure development environments Experience with using and deploying LLMs Knowledge of NLP literature, thrust areas, conference venues, and code repositories Familiarity with both open-source and OpenAI LLMs and RAG architecture Familiarity with UI tools like Streamlit, Flask, FAST APIs, Rest APIs, Docker containers Understanding of common NLP tasks such as text classification, entity recognition, entity extraction, and question answering Proficiency in multiple machine learning and AI techniques such as supervised, unsupervised, reinforcement learning, deep learning, and NLP Proficient in Python and one of PySpark. Familiarity with python tools for data processing Proficiency in libraries such as Hugging Face and OpenAI API Proficiency in Python, R, or other programming languages for data analysis and AI/ML development Proven hands-on skills with repository management and GPU use, and the ability to rapidly set up NLP pipelines for testing new ideas Proven ability to develop and deploy data pipelines, machine learning models, or applications on cloud platforms (Azure, Databricks, AzureML) Proven excellent analytical and problem-solving skills, including the ability to disaggregate issues, identify root causes, and recommend solutions At UnitedHealth Group, our mission is to help people live healthier lives and make the health system work better for everyone. We believe everyone-of every race, gender, sexuality, age, location and income-deserves the opportunity to live their healthiest life. Today, however, there are still far too many barriers to good health which are disproportionately experienced by people of color, historically marginalized groups and those with lower incomes. We are committed to mitigating our impact on the environment and enabling and delivering equitable care that addresses health disparities and improves health outcomes - an enterprise priority reflected in our mission.

Optum is a global organization that delivers care, aided by technology to help millions of people live healthier lives. The work you do with our team will directly improve health outcomes by connecting people with the care, pharmacy benefits, data and resources they need to feel their best. Here, you will find a culture guided by inclusion, talented peers, comprehensive benefits and career development opportunities. Come make an impact on the communities we serve as you help us advance health optimization on a global scale. Join us to start Caring. Connecting. Growing together. At Optum AI, we leverage data and resources to make a significant impact on the healthcare system. Our solutions have the potential to improve healthcare for everyone. We work on cutting-edge projects involving ML, NLP, and LLM techniques, continuously developing and improving generative AI methods for structured and unstructured healthcare data. Our team collaborates with world-class experts and top universities to develop innovative AI/ML solutions, often leading to patents and published papers. Primary Responsibilities Develop and run pipelines for data ingress and model output egress Develop and run scripts for ML model inference Design, implement, and maintain CI/CD pipelines for MLOps and DevOps functions Identify technical problems and develop software updates and fixes Develop scripts or tools to automate repetitive tasks Automate the provisioning and configuration of infrastructure resources Provide guidance on the best use of specific tools or technologies to achieve desired results Create documentation for infrastructure design and deployment procedures Utilize AI/ML frameworks and tools such as MLFlow, TensorFlow, PyTorch, Keras, Scikit-learn, etc. Lead and manage AI/ML teams and projects from ideation to delivery and evaluation Apply expertise in various AI/ML techniques, including deep learning, NLP, computer vision, recommender systems, reinforcement learning, and large language models Communicate complex AI/ML concepts and results to technical and non-technical audiences effectively Comply with the terms and conditions of the employment contract, company policies and procedures, and any and all directives (such as, but not limited to, transfer and/or re-assignment to different work locations, change in teams and/or work shifts, policies in regards to flexibility of work benefits and/or work environment, alternative work arrangements, and other decisions that may arise due to the changing business environment). The Company may adopt, vary or rescind these policies and directives in its absolute discretion and without any limitation (implied or otherwise) on its ability to do so Required Qualifications Bachelor's degree or higher in computer science engineering with a focus on language processing 6+ years of experience in AI/ML roles Experience with Azure development environments Experience with using and deploying LLMs Experience in developing solutions in the NLP space and relevant projects Proficiency in multiple machine learning and AI techniques such as supervised, unsupervised, reinforcement learning, deep learning, and NLP Proficient in Python and one of PySpark or Scala Familiarity with python tools for data processing Proficiency in libraries such as Hugging Face and OpenAI API Proficiency in Python, R, or other programming languages for data analysis and AI/ML development Familiarity with both open-source and OpenAI LLMs and RAG architecture Familiarity with UI tools like Streamlit, Flask, FAST APIs, Rest APIs, Docker containers Understanding of common NLP tasks such as text classification, entity recognition, entity extraction, and question answering Knowledge of NLP literature, thrust areas, conference venues, and code repositories Hands-on skills with repository management and GPU use, and the ability to rapidly set up NLP pipelines for testing new ideas Proven excellent analytical and problem-solving skills, including the ability to disaggregate issues, identify root causes, and recommend solutions Ability to develop and deploy data pipelines, machine learning models, or applications on cloud platforms (Azure, Databricks, AzureML) DevOps Skills: Experience building and maintaining CI/CD pipelines Experience with DevOps tools (GitHub, GitHub Actions, Azure devops, Kubernetes, etc) Experience with data-oriented workflow orchestration frameworks (Airflow, kafka, etc) Security and vulnerability management Familiarity with traditional software monitoring, scaling, and quality management (QMS) Preferred Qualifications Experience deploying and maintaining ML models in production Experience with model observability tools for insights into the behavior, performance, and health of deployed ML models (tracking, alerting, compliance monitoring, etc) MLOps skills Familiarity with model versioning tools (MLFlow, etc) Familiarity with data versioning tools (Delta Lake, DVC, LakeFS, etc) At UnitedHealth Group, our mission is to help people live healthier lives and make the health system work better for everyone. We believe everyone-of every race, gender, sexuality, age, location and income-deserves the opportunity to live their healthiest life. Today, however, there are still far too many barriers to good health which are disproportionately experienced by people of color, historically marginalized groups and those with lower incomes. We are committed to mitigating our impact on the environment and enabling and delivering equitable care that addresses health disparities and improves health outcomes - an enterprise priority reflected in our mission.

Job Title: AI/ML Engineer Location: 100% Remote Job Type: Full-Time About the Role: We are seeking a highly skilled and motivated AI/ML Engineer to design, develop, and deploy cutting-edge ML models and data-driven solutions. You will work closely with data scientists, software engineers, and product teams to bring AI-powered products to life and scale them effectively. Key Responsibilities: Design, build, and optimize machine learning models for classification, regression, recommendation, and NLP tasks. Collaborate with data scientists to transform prototypes into scalable, production-ready models. Deploy, monitor, and maintain ML pipelines in production environments. Perform data preprocessing, feature engineering, and selection from structured and unstructured data. Implement model performance evaluation metrics and improve accuracy through iterative tuning. Work with cloud platforms (AWS, Azure, GCP) and MLOps tools to manage model lifecycle. Maintain clear documentation and collaborate cross-functionally across teams. Stay updated with the latest ML/AI research and technologies to continuously enhance our solutions. Required Qualifications: Bachelor’s or Master’s degree in Computer Science, Data Science, Engineering, or a related field. 2–5 years of experience in ML model development and deployment. Proficient in Python and libraries such as scikit-learn, TensorFlow, PyTorch, pandas, NumPy, etc. Strong understanding of machine learning algorithms, statistical modeling, and data analysis. Experience with building and maintaining ML pipelines using tools like MLflow, Kubeflow, or Airflow. Familiarity with containerization (Docker), version control (Git), and CI/CD for ML models. Experience with cloud services such as AWS SageMaker, GCP Vertex AI, or Azure ML.

Job Description We are seeking individuals with advanced expertise in Machine Learning (ML) to join our dynamic team. As an Applied AI ML Lead within our Corporate Sector, you will play a pivotal role in developing machine learning and deep learning solutions, and experimenting with state of the art models. You will contribute to our innovative projects and drive the future of machine learning at AI Technologies. You will use your knowledge of ML tools and algorithms to deliver the right solution. You will be a part of an innovative team, working closely with our product owners, data engineers, and software engineers to build new AI/ML solutions and productionize them. You will also mentor other AI engineers and scientists while fostering a culture of continuous learning and technical excellence. We are looking for someone with a passion for data, ML, and programming, who can build ML solutions at-scale with a hands-on approach with detailed technical acumen. Job Responsibilities Serve as a subject matter expert on a wide range of machine learning techniques and optimizations. Provide in-depth knowledge of machine learning algorithms, frameworks, and techniques. Enhance machine learning workflows through advanced proficiency in large language models (LLMs) and related techniques. Conduct experiments using the latest machine learning technologies, analyze results, and tune models. Engage in hands-on coding to transition experimental results into production solutions by collaborating with the engineering team, owning end-to-end code development in Python for both proof of concept/experimentation and production-ready solutions. Optimize system accuracy and performance by identifying and resolving inefficiencies and bottlenecks, collaborating with product and engineering teams to deliver tailored, science and technology-driven solutions. Integrate Generative AI within the machine learning platform using state-of-the-art techniques, driving decisions that influence product design, application functionality, and technical operations and processes Required Qualifications, Capabilities, And Skills Formal training or certification on AI/ML concepts and 5+ years applied experience Hans on experience in programming languages, particularly Python. Manage to apply data science and machine learning techniques to address business challenges. Strong background in Natural Language Processing (NLP) and Large Language Models (LLMs). Expertise in deep learning frameworks such as PyTorch or TensorFlow, and advanced applied ML areas like GPU optimization, finetuning, embedding models, inferencing, prompt engineering, evaluation, and RAG (Similarity Search). Manage to complete tasks and projects independently with minimal supervision, with a passion for detail and follow-through. Excellent communication skills, team player, and demonstrated leadership in collaborating effectively with engineers, product managers, and other ML practitioners Preferred Qualifications, Capabilities, And Skills Exposure with Ray, MLFlow, and/or other distributed training frameworks. MS and/or PhD in Computer Science, Machine Learning, or a related field. Understanding of Search/Ranking, Recommender systems, Graph techniques, and other advanced methodologies. Familiar in Reinforcement Learning or Meta Learning. Understanding of Large Language Model (LLM) techniques, including Agents, Planning, Reasoning, and other related methods. Exposure building and deploying ML models on cloud platforms such as AWS and AWS tools like Sagemaker, EKS, etc. About Us JPMorganChase, one of the oldest financial institutions, offers innovative financial solutions to millions of consumers, small businesses and many of the world’s most prominent corporate, institutional and government clients under the J.P. Morgan and Chase brands. Our history spans over 200 years and today we are a leader in investment banking, consumer and small business banking, commercial banking, financial transaction processing and asset management. We offer a competitive total rewards package including base salary determined based on the role, experience, skill set and location. Those in eligible roles may receive commission-based pay and/or discretionary incentive compensation, paid in the form of cash and/or forfeitable equity, awarded in recognition of individual achievements and contributions. We also offer a range of benefits and programs to meet employee needs, based on eligibility. These benefits include comprehensive health care coverage, on-site health and wellness centers, a retirement savings plan, backup childcare, tuition reimbursement, mental health support, financial coaching and more. Additional details about total compensation and benefits will be provided during the hiring process. We recognize that our people are our strength and the diverse talents they bring to our global workforce are directly linked to our success. We are an equal opportunity employer and place a high value on diversity and inclusion at our company. We do not discriminate on the basis of any protected attribute, including race, religion, color, national origin, gender, sexual orientation, gender identity, gender expression, age, marital or veteran status, pregnancy or disability, or any other basis protected under applicable law. We also make reasonable accommodations for applicants’ and employees’ religious practices and beliefs, as well as mental health or physical disability needs. Visit our FAQs for more information about requesting an accommodation. JPMorgan Chase & Co. is an Equal Opportunity Employer, including Disability/Veterans About The Team Our professionals in our Corporate Functions cover a diverse range of areas from finance and risk to human resources and marketing. Our corporate teams are an essential part of our company, ensuring that we’re setting our businesses, clients, customers and employees up for success.

Job Title: Data Engineer – AWS, PySpark, Databricks Location: Mumbai (Bandra kurla complex ) Experience Required: 5+ Years Employment Type: Contract Job Overview We are seeking a highly skilled Data Engineer with strong hands-on experience in AWS cloud services , PySpark , and Databricks to join our advanced analytics and data platform team. The ideal candidate should have expertise in building scalable data pipelines, transforming large datasets, and managing cloud-based big data environments. You’ll work closely with data scientists, architects, and business teams to deliver efficient data solutions. Key Responsibilities Design, develop, and maintain robust ETL/ELT pipelines using PySpark on Databricks. Work with structured and semi-structured data on large-scale data platforms. Integrate data from various sources into the AWS data lake and Delta Lake. Optimize Spark jobs for performance, cost, and reliability. Collaborate with business stakeholders to understand data requirements and translate them into scalable solutions. Use AWS services (S3, Glue, Lambda, EMR, Redshift, Athena) to manage data pipelines and orchestrations. Write clean, maintainable, and reusable PySpark code with proper logging and error handling. Implement data governance, quality checks, and documentation practices. Perform data validation and reconciliation to ensure accuracy and consistency. Participate in code reviews, unit testing, and continuous integration/delivery processes. Required Skills & Qualifications 5+ years of experience in data engineering or big data development. Minimum 3+ years of experience working with PySpark and Apache Spark. Strong experience working on Databricks (Notebooks, Workflows, Delta Lake). Proficiency with AWS services: S3, Lambda, Glue, EMR, Redshift, and Athena. Expertise in working with large-scale data ingestion, transformation, and storage. Solid understanding of data partitioning, file formats (Parquet, ORC, JSON), and performance tuning in Spark. Experience in CI/CD practices, version control (Git), and deployment automation. Familiarity with Airflow, DBT, or other workflow orchestration tools is a plus. Strong communication and collaboration skills in agile environments. Good To Have Experience with Delta Lake architecture and advanced Databricks features. Knowledge of SQL optimization and data warehousing concepts. Experience integrating with BI tools like Power BI or Tableau. Exposure to machine learning pipelines or integration with MLflow. AWS certifications (e.g., AWS Certified Data Analytics, Solutions Architect). Skills: data governance,data quality,athena,aws,databricks,git,python,emr,lambda,dbt,etl,redshift,sql,airflow,ci/cd,data warehousing,pyspark,elt,glue,s3,spark

We are also looking for a collaborative and results-driven AI & DevOps Engineer with expertise in deploying scalable ML pipelines, integrating LLMs, and orchestrating end-to-end AI workflows across cloud platforms such as AWS and Azure. Technical Skill Highlights: Hands-on experience with AWS (EC2, S3, Lambda), Azure (AKS, API Management). Expertise in CI/CD (GitLab, GitHub Actions), Terraform, Docker, Kubernetes, DevSecOps. Experience with MLflow, LLMOps pipelines, LangChain, LangGraph, Prompt Engineering, LLM integration. Proficiency with vector databases (PGVector, Pinecone, FAISS, etc.). Strong Python skills and version control with Git. Experience collaborating in Agile/Scrum teams and cross-team setups. Professional Strengths: Deployed production-ready LLM-powered features using LangChain and LangGraph. Designed cloud-native infrastructure using Terraform and containerization. Integrated LLMs with vector databases for Retrieval-Augmented Generation (RAG) workflows. Developed and scaled ML pipelines for enterprise use. Streamlined DevOps/MLOps practices, enhancing CI/CD/CT efficiency. Local candidates only Work from office only Job Types: Full-time, Permanent Pay: ₹50,000.00 - ₹100,000.00 per month Benefits: Provident Fund Schedule: Day shift Experience: AI & DevOps Engineer: 4 years (Preferred) Work Location: In person Speak with the employer +91 9056488440

JOB DESCRIPTION We are seeking individuals with advanced expertise in Machine Learning (ML) to join our dynamic team. As an Applied AI ML Lead within our Corporate Sector, you will play a pivotal role in developing machine learning and deep learning solutions, and experimenting with state of the art models. You will contribute to our innovative projects and drive the future of machine learning at AI Technologies. You will use your knowledge of ML tools and algorithms to deliver the right solution. You will be a part of an innovative team, working closely with our product owners, data engineers, and software engineers to build new AI/ML solutions and productionize them. You will also mentor other AI engineers and scientists while fostering a culture of continuous learning and technical excellence. We are looking for someone with a passion for data, ML, and programming, who can build ML solutions at-scale with a hands-on approach with detailed technical acumen. Job responsibilities Serve as a subject matter expert on a wide range of machine learning techniques and optimizations. Provide in-depth knowledge of machine learning algorithms, frameworks, and techniques. Enhance machine learning workflows through advanced proficiency in large language models (LLMs) and related techniques. Conduct experiments using the latest machine learning technologies, analyze results, and tune models. Engage in hands-on coding to transition experimental results into production solutions by collaborating with the engineering team, owning end-to-end code development in Python for both proof of concept/experimentation and production-ready solutions. Optimize system accuracy and performance by identifying and resolving inefficiencies and bottlenecks, collaborating with product and engineering teams to deliver tailored, science and technology-driven solutions. Integrate Generative AI within the machine learning platform using state-of-the-art techniques, driving decisions that influence product design, application functionality, and technical operations and processes Required qualifications, capabilities, and skills Formal training or certification on AI/ML concepts and 5+ years applied experience Hans on experience in programming languages, particularly Python. Manage to apply data science and machine learning techniques to address business challenges. Strong background in Natural Language Processing (NLP) and Large Language Models (LLMs). Expertise in deep learning frameworks such as PyTorch or TensorFlow, and advanced applied ML areas like GPU optimization, finetuning, embedding models, inferencing, prompt engineering, evaluation, and RAG (Similarity Search). Manage to complete tasks and projects independently with minimal supervision, with a passion for detail and follow-through. Excellent communication skills, team player, and demonstrated leadership in collaborating effectively with engineers, product managers, and other ML practitioners Preferred qualifications, capabilities, and skills Exposure with Ray, MLFlow, and/or other distributed training frameworks. MS and/or PhD in Computer Science, Machine Learning, or a related field. Understanding of Search/Ranking, Recommender systems, Graph techniques, and other advanced methodologies. Familiar in Reinforcement Learning or Meta Learning. Understanding of Large Language Model (LLM) techniques, including Agents, Planning, Reasoning, and other related methods. Exposure building and deploying ML models on cloud platforms such as AWS and AWS tools like Sagemaker, EKS, etc. ABOUT US JPMorganChase, one of the oldest financial institutions, offers innovative financial solutions to millions of consumers, small businesses and many of the world’s most prominent corporate, institutional and government clients under the J.P. Morgan and Chase brands. Our history spans over 200 years and today we are a leader in investment banking, consumer and small business banking, commercial banking, financial transaction processing and asset management. We offer a competitive total rewards package including base salary determined based on the role, experience, skill set and location. Those in eligible roles may receive commission-based pay and/or discretionary incentive compensation, paid in the form of cash and/or forfeitable equity, awarded in recognition of individual achievements and contributions. We also offer a range of benefits and programs to meet employee needs, based on eligibility. These benefits include comprehensive health care coverage, on-site health and wellness centers, a retirement savings plan, backup childcare, tuition reimbursement, mental health support, financial coaching and more. Additional details about total compensation and benefits will be provided during the hiring process. We recognize that our people are our strength and the diverse talents they bring to our global workforce are directly linked to our success. We are an equal opportunity employer and place a high value on diversity and inclusion at our company. We do not discriminate on the basis of any protected attribute, including race, religion, color, national origin, gender, sexual orientation, gender identity, gender expression, age, marital or veteran status, pregnancy or disability, or any other basis protected under applicable law. We also make reasonable accommodations for applicants’ and employees’ religious practices and beliefs, as well as mental health or physical disability needs. Visit our FAQs for more information about requesting an accommodation. JPMorgan Chase & Co. is an Equal Opportunity Employer, including Disability/Veterans ABOUT THE TEAM Our professionals in our Corporate Functions cover a diverse range of areas from finance and risk to human resources and marketing. Our corporate teams are an essential part of our company, ensuring that we’re setting our businesses, clients, customers and employees up for success.