Manager AI/ML Engineering - LifeScience or Diagnostics

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.

Optum AI is UnitedHealth Group’s enterprise AI team. We are AI/ML scientists and engineers with deep expertise in AI/ML engineering for health care. We develop AI/ML solutions for the highest impact opportunities across UnitedHealth Group businesses including UnitedHealthcare, Optum Financial, Optum Health, Optum Insight, and Optum Rx. In addition to transforming the health care journey through responsible AI/ML innovation, our charter also includes developing and supporting an enterprise AI/ML development platform.

Optum AI team members:

• Have impact at scale: We have the data and resources to make an impact at scale. When our solutions are deployed, they have the potential to make health care system work better for everyone
• Do ground-breaking work: Many of our current projects involve cutting edge ML, NLP and LLM techniques. Generative AI methods for working with structured and unstructured health care data are continuously being developed and improved. We are working in one of the most important frontiers of AI/ML research and development
• Partner with world-class experts on innovative solutions: Our team members are developing novel AI/ML solutions to business challenges. In some cases, this includes the opportunity to file patents and publish papers about the methods we develop. We also collaborate with AI/ML researchers at some of the world’s top universities

Primary Responsibilities:

• Design, develop, and deploy advanced GenAI and NLP solutions to solve complex business and healthcare problems, using state-of-the-art transformer models, LLMs, and modern ML frameworks
• Lead research, evaluation, and integration of new LLMs (GPT, Claude, Gemini, Anthropic), vector search technologies, prompt-engineering techniques, and enterprise GenAI platforms
• Build and optimize Retrieval-Augmented Generation (RAG) systems using vector databases (FAISS, Pinecone, Chroma), improving grounding, retrieval accuracy, and overall system reliability
• Architect and implement agentic AI workflows using frameworks like LangGraph, AutoGen, CrewAI, or Semantic Kernel, enabling single-agent and multi-agent systems for reasoning, planning, and tool-calling
• Drive the development of high-quality NLP pipelines-including tokenization, embeddings, seq-to’seq models, evaluation metrics, and domain adaptation-with a focus on performance, scalability, and robustness
• Perform advanced data analysis, preprocessing, and feature engineering to ensure data quality, reduce noise, and improve model reliability
• Develop and maintain scalable big-data pipelines for ingestion, processing, and analysis, working with structured and unstructured datasets
• Optimize model inference, latency, and throughput, including integration with LLM gateways, guardrails, filters, and enterprise evaluation frameworks
• Lead experimentation cycles, comparing model variants, evaluating prompt strategies, measuring LLM performance, and driving data- and metric-driven decision-making
• Collaborate with data engineering, platform, ML, product, and domain teams to identify AI opportunities and translate them into actionable technical solutions
• Author high-quality design documents, evaluation reports, model cards, and reproducible research artifacts
• Mentor junior ML/GenAI engineers on best practices in prompt engineering, RAG design, NLP experimentation, and responsible AI principles
• Stay ahead of the rapidly evolving GenAI/NLP landscape-LLM releases, vector search innovations, evaluation techniques, and agentic frameworks-and introduce relevant capabilities to the organization
• Support deployment of production-grade GenAI systems with attention to monitoring, drift detection, safety, and ongoing reliability
• Comply with company policies, employment terms, and organizational directives.
  Comply with the terms and conditions of the employment contract, company polic…