Job Description

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.

Primary Responsibilities:

• Generative AI Application Development:
  • Design, build, and deploy features using Large Language Models (LLMs), including conversational AI, summarization, and knowledge extraction
  • Implement and optimize Retrieval-Augmented Generation (RAG) pipelines, from data preprocessing and embedding to vector search
  • Apply advanced prompt engineering, fine-tuning (e.g., LoRA), and other model adaptation techniques to enhance performance and accuracy
• Machine Learning Model Development & Deployment:
  • Develop and productionize a range of machine learning models, including both traditional ML (e.g., regression, classification, clustering) and deep learning models
  • Conduct feature engineering on large-scale datasets to create robust inputs for model training
  • Establish and manage processes for model evaluation, performance monitoring, and continuous retraining
• AI Systems & Integration:
  • Build and maintain scalable services that integrate with third-party AI APIs (e.g., OpenAI, Azure) and open-source models
  • Develop agentic workflows that orchestrate multiple tools, models, and data sources to solve complex problems
  • Work with vector databases (e.g., Pinecone, pgvector) and implement caching strategies to ensure low-latency performance
• Collaboration & AI Quality:
  • Partner with product, data, and engineering teams to translate business needs into deployable AI/ML features
  • Implement guardrails and other techniques to improve model reliability and reduce issues like hallucination
  • Participate in code reviews, design discussions, and contribute to the team's Responsible AI practices
• 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:

• 8+ years of professional experience in Data Science, including 2+ years of hands-on experience building and deploying AI/ML solutions in a production environment
• Core Programming & Data Skills:
  • Experience with large-scale data processing and feature engineering
  • Solid proficiency in Python & Pyspark for ML and backend development
• Generative AI Expertise:
  • Proven experience developing applications using LLMs (e.g., GPT series, Llama) and common frameworks (e.g., LangChain, LlamaIndex)
  • Practical knowledge of prompt engineering, RAG, and model fine-tuning
• Machine Learning Foundations:
  • Hands-on experience building, training, and evaluating ML models
  • Solid understanding of both supervised and unsupervised learning, deep learning fundamentals, and statistical principles
• Cloud & Communication:
  • Experience with at least one major cloud AI platform (e.g. AWS SageMaker, Google Vertex AI)
  • Proven solid ability to communicate complex technical concepts to both technical and non-technical stakeholders

Preferred Qualifications:

• Hands-on experience with MLOps practices, including CI/CD for ML, model monitoring, and containerization (Docker, Kubernetes)
• Experience with distributed computing for ML (e.g., Spark)
• Familiarity with multimodal AI (handling text, image, or speech data)
• A proven ability to connect ML solutions to tangible business outcomes and product improvements

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.