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At Optum, we value the distinctive talents and perspectives each employee brings to our workplace. We foster an inclusive work environment through various initiatives like our Employee Resource Groups, which are connected internal communities that focus on sharing our diverse experiences and backgrounds, creating a greater sense of belonging.
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Optum

Optum partners with The Blind Relief Association (TBRA) Delhi

Optum partners with Sarthak Educational Trust

Building an inclusive workplace - Optum India

UHG Employee Value Proposition

About Us: 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 Proficiency in Python, R, or other programming languages for data analysis and AI/ML development 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 regard 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 2+ years of experience in AI/ML roles Hands on experience containerization, and deploy LLM applications in cloud environments using Docker, Podman, Kubernetes, and MLOps pipelines, integrating services such as Azure OpenAI, AWS Sagemaker, or Vertex AI for scalable, secure, and cost-optimized GenAI tool deployment with continuous monitoring and CI/CD automation Experience in developing solutions in the NLP space and relevant projects. Hands-on experience with NLP tasks: text classification, named entity recognition/extraction, semantic search, summarization, and question answering. Hands on experience in frameworks like LangChain, LlamaIndex, Hugging Face Transformers, LangGraph, CrewAI, Autogen etc. Experience with Azure development environments Proficiency in supervised, unsupervised, reinforcement learning, deep learning, and transformer-based architectures Good understanding of LLMs (OpenAI, Hugging Face, etc.), MCP server, Retrieval-Augmented Generation (RAG) architectures and vector databases (FAISS, Pinecone, Weaviate etc) Proficient in Python and one of PySpark or Scala. Familiarity with python tools for data processing Ability to develop and deploy data pipelines, machine learning models, or applications on cloud platforms (Azure, Databricks, AzureML) Knowledge of NLP literature, thrust areas, conference venues, and code repositories Familiarity with UI tools like Streamlit, Chainlit, and API Frameworks like Flask, FAST APIs, Rest APIs etc.. Proficiency in libraries such as Hugging Face and OpenAI API. Proven excellent analytical and problem-solving skills, including the ability to disaggregate issues, identify root causes, and recommend solutions Hands-on skills with repository management and GPU use, and the ability to rapidly set up NLP pipelines for testing new ideas Familiarity with OCR based AI application using tools like Tesseract, Amazon Textract, Azure Form Recognizer, etc. for extracting data from scanned or image-based PDFs DevOps Skills:Experience building and maintaining CI/CD pipelines for ML and GenAI applications Hands-on experience with containerization and orchestration using Docker and/or Podman Familiarity with traditional software monitoring, scaling, and quality management (QMS) 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 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.)

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