Lead AI/ML Engineer - Office Based - Eden Prairie, MN

UnitedHealth Group•Eden Prairie, MN

1d•$145,500 - $249,500•Onsite

About The Position

As a Lead AI/ML Engineer on the Optum Technology team, you will drive the design, development, and deployment of enterprise-grade machine learning models and artificial intelligence solutions. You will lead engineering initiatives, build robust MLOps platforms, and use emerging AI technologies to support healthcare outcomes. Working with data scientists, software engineers, and product leaders, you will deliver scalable, reliable, and responsible AI solutions across the enterprise.

Requirements

B.S./B.E./BTECH/MCA in CSE/IT or equivalent experience.
7+ years of professional software engineering experience.
4+ years building, deploying, and maintaining ML models in production environments.
3+ years leading engineering projects or providing technical guidance to software or ML engineering teams.
3+ years designing MLOps architectures, containerization (e.g., Docker, Kubernetes), and cloud infrastructure (e.g., AWS, Azure, or GCP).
3+ years building CI/CD automated pipelines and model monitoring systems for production software.
2+ years of hands-on programming experience with Python and core ML libraries/frameworks (e.g., PyTorch, TensorFlow, Scikit-learn).

Nice To Haves

Master’s degree or higher in Computer Science, Data Science, Artificial Intelligence, or a related quantitative field.
Experience developing applications using Generative AI, large language models (LLMs), retrieval-augmented generation (RAG), or agentic workflows.
Experience with high-throughput distributed computing platforms (e.g., Apache Spark, Ray) and vector database technologies.
Knowledge of responsible AI frameworks, bias mitigation techniques, and enterprise data privacy compliance.

Responsibilities

Architect, build, and deploy scalable machine learning and artificial intelligence models and MLOps pipelines in production environments.
Lead engineering teams in designing model training, deployment, inference, and monitoring architectures using modern cloud platforms.
Evaluate emerging AI/ML techniques, frameworks, and foundational models to inform technology improvements and innovation.
Collaborate with software engineering, data science, and product leadership to translate business requirements into production-ready capabilities.
Establish best practices for code quality, CI/CD, data pipelines, model governance, and responsible AI.
Provide technical mentorship and guidance to software and ML engineers.