Senior AI ML Engineer

Requisition Number: 2362481
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.
About the Role
We are seeking a AI/ML Engineer to help design, build, and optimize generative AI-powered applications. This role combines hands on development with applied AI problem solving, focusing on implementing LLM capabilities, retrieval workflows, and efficient AI integrations. You will collaborate closely with senior engineers and product teams to translate requirements into practical, scalable solutions.
Primary Responsibilities:

• AI Applications & Feature Development
  • Develop and refine LLM-based features such as chat, summarization, knowledge search, and data extraction
  • Apply prompt engineering techniques and support model fine tuning or parameter efficient tuning (e.g., LoRA)
  • Implement RAG (retrieval augmented generation) workflows including preprocessing, embedding generation, and vector search
• Model & Architecture Understanding
  • Work with transformer-based models; apply foundational understanding of attention, embeddings, and model behavior
  • Assist in model interpretability and improving reliability of model outputs
• AI Quality, Evaluation & Safety
  • Help improve accuracy by reducing hallucinations through prompting, guardrails, and retrieval improvements
  • Support benchmarking, evaluation tests, and quality checks
  • Contribute to Responsible AI practices
• Integration & Orchestration
  • Build services integrating AI APIs (OpenAI, Azure, open source LLMs)
  • Implement tool/agent orchestration flows with guidance from senior team members
  • Work with vector databases such as FAISS, Pinecone, or pgvector
• Performance & Optimization
  • Contribute to enhancements in latency, throughput, and token efficiency
  • Support implementation of model compression and quantization techniques
  • Develop caching and batching strategies to improve system performance
• Collaboration & Delivery
  • Work closely with product, data, and engineering teams to deliver high quality AI features
  • Participate in code reviews, team design discussions, and knowledge sharing
• 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 equivalent experience
• Proven skills
  • Agentic AI, GenAI & LLMs: GPT based solutions, prompt engineering, agentic AI, AI Agents, Multi agent frameworks
  • Programming: Python (primary)
  • ML Foundations: Supervised & unsupervised learning, deep learning fundamentals
  • Statistics: Probability, optimization, experimental methodologies
  • Model Development: Build, train, evaluate, and tune ML models
  • Data Handling: Large scale data processing & feature engineering
  • AI Domains: NLP / NLU (intent classification, semantic understanding)
  • Communication: Ability to explain AI/ML outcomes to business & leadership
  • Cloud AI: Azure AI services, enterprise AI platform, AWS, GCP

Preferred Qualifications:

• Production ML: Hands on experience in deploying ML models to production
• MLOps: Experience with CI/CD for ML, model monitoring, lifecycle management, Dockers, Kubernetes, JFrog
• Distributed Systems: Experience with Spark based ML, scalable data platforms
• Multimodal AI: Experience with computer vision, speech recognition (ASR)
• Proven product Mindset: Adapting ML to real world business decisioning

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.