Lead AI/ML Engineer- Eden Prairie, MN

UnitedHealth Group•Eden Prairie, MN
•$145,500 - $249,500•Onsite

About The Position

Optum Tech is a global leader in health care innovation. Our teams develop cutting-edge solutions that help people live healthier lives and help make the health system work better for everyone. From advanced data analytics and AI to cybersecurity, we use innovative approaches to solve some of health care’s most complex challenges. Your contributions here have the potential to change lives. Ready to build the next breakthrough? Join us in making healthcare work better for everyone through people-led, responsible AI while Caring. Connecting. Growing together. Welcome to the Optum Health AI team! Our mission is to leverage cutting-edge AI technologies to transform healthcare operations, improve patient experience, and enhance scalability. This role focuses primarily on Voice AI—a high-visibility, key strategic initiative under Optum Health AI designed to create a seamless experience for members and agents, reduce manual work, and improve scalability. As a Lead AI/ML Engineer, you will establish foundational capabilities such as language translation, accent harmonization, and real-time transcription. These advanced capabilities will cross-pollinate across all Optum Health AI pillars (including Provider Scheduling, Prior Authorization, Summarization, and more) while setting enterprise-wide standards for external vendor evaluations. Partnering closely with ECS Business, you will lead the estimates, solution architecture, roadmap alignment, and engineering to deliver production-ready prototypes that are reusable, scalable, secure, and compliant.

Requirements

  • Bachelor’s degree in Computer Science, Engineering, Data Science, Artificial Intelligence, or a related technical field; 4+ years of software engineering experience may substitute for a degree
  • 10+ years of software engineering experience, including designing, building, and deploying production-grade AI/ML models and systems
  • 3+ years of experience leading engineering teams, mentoring engineers, defining technical standards, and driving solution architecture
  • 4+ years of experience developing applications leveraging Large Language Models (LLMs), LLM workflows, Agentic AI, evaluation techniques, and observability platforms
  • Experience with Python, backend services, cloud platforms, and CI/CD pipelines to deliver scalable, secure, production-ready solutions

Nice To Haves

  • Master’s or Ph.D. degree in Computer Science, Data Science, Artificial Intelligence, or a related technical field
  • Technical experience with Databricks, Azure AI, Azure Transcription Services, RLlib, PyTorch, OpenAI, or similar AI/ML platforms and frameworks
  • Experience developing with front-end frameworks, REST/WebSocket APIs, and secure cloud-native application patterns
  • Experience working in healthcare, including EHR integration and HIPAA-compliant AI application development
  • Deep machine learning domain knowledge across NLP, speech, personalization, recommendation systems, computer vision, or anomaly detection
  • Demonstrated adaptability, ownership, learning agility, and curiosity in solving ambiguous, high-impact technical problems

Responsibilities

  • Lead and mentor AI/ML engineers, setting technical direction, engineering standards, and a culture of continuous learning
  • Design, build, and deploy responsible Voice AI capabilities, including speech handling, enhanced ASR, bilingual switching, slurred speech recognition, dynamic personality, and multi-modal/multi-cloud interactions
  • Translate AI advances in real-time transcription and speech processing into scalable, reusable, production-ready enterprise capabilities
  • Partner with ECS Business to drive solution architecture, cost estimation, and roadmap alignment across modern and legacy technology stacks
  • Embed ethical AI and HIPAA-compliant security standards across the model development lifecycle
  • Implement advanced engineering features such as dynamic interactive forms, adaptive updates, and conditional logic to improve patient-agent workflows
  • Define enterprise standards for evaluating and vetting external AI vendors
  • Use enterprise-approved AI tools to automate workflows, accelerate delivery, and drive continuous improvement

Benefits

  • comprehensive benefits package
  • incentive and recognition programs
  • equity stock purchase
  • 401k contribution
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