Lead AI/ML Engineer in Minneapolis, MN or Chicago, IL

UnitedHealth Group•Minneapolis, MN

3d•$145,500 - $249,500

About The Position

Optum Tech’s Platform, AI & Integration (PAII) team leads the design, delivery, and enterprise integration of AI/ML capabilities across its Cloud Platform. The Lead AI/ML Engineer serves as a primary technical and people leader, driving architecture, engineering standards, and deployment of machine learning models, intelligent services, and automation frameworks in core platform operations. The role works across cloud infrastructure, advanced data pipelines, and scalable artificial intelligence to develop robust, secure, and reliable AI solutions at enterprise scale. The role includes leading the PAII engineering team, guiding end-to-end AI/ML development and production deployment, integrating AI capabilities with cloud and data services, and advancing the platform AI roadmap and MLOps practices. The engineer also evaluates emerging technologies, promotes responsible AI, uses enterprise-approved AI tools to improve engineering workflows, develops team capabilities, and collaborates with Platform, Data, and Security teams. The position is listed in Minneapolis, Minnesota, or Chicago, Illinois. The annual salary range is $145,500–$249,500 based on full-time employment. Benefits include a comprehensive benefits package, incentive and recognition programs, an employee stock purchase plan, and 401(k) contribution, subject to eligibility requirements. Candidates must pass a drug test before beginning employment.

Requirements

At least 7 years of software engineering, data engineering, or machine learning engineering experience.
At least 4 years of hands-on experience designing, training, deploying, and maintaining AI/ML models or intelligent services in production environments.
At least 3 years of technical or people leadership experience guiding engineering teams.
At least 3 years of experience with cloud platforms such as Azure, AWS, or GCP and cloud-native architecture.
At least 3 years of programming experience in Python and using standard machine learning frameworks such as PyTorch, TensorFlow, or scikit-learn.
At least 2 years of experience implementing MLOps practices, automated CI/CD pipelines, and model monitoring or validation frameworks.

Nice To Haves

Bachelor's or Master's degree in Computer Science, Data Science, Artificial Intelligence, Engineering, or a related technical field.
Experience with generative AI technologies, large language models (LLMs), prompt engineering, or retrieval-augmented generation (RAG) architectures.
Experience implementing AI governance, model security, and responsible AI frameworks in an enterprise or regulated healthcare setting.
Experience with containerization and orchestration platforms such as Docker and Kubernetes.
Experience building scalable microservices, RESTful APIs, and distributed event-driven data streaming systems such as Apache Kafka.
Demonstrated ability to manage stakeholders and communicate complex technical concepts to cross-functional business partners.

Responsibilities

Provide technical and people leadership for the PAII engineering team, establishing engineering standards, best practices, and architectural direction.
Design, develop, and deploy AI-powered solutions for complex business challenges, emphasizing responsible AI use.
Own end-to-end AI/ML model development, validation, and production deployment, embedding intelligent services and automation securely and reliably into core platform operations.
Integrate AI/ML capabilities with cloud platform services, infrastructure components, and modern data pipelines.
Drive the platform AI roadmap, architecture decisions, and MLOps practices to sustain delivery and scale.
Evaluate emerging trends to inform solution design and strategic innovation across platform and AI engineering initiatives.
Use enterprise-approved AI tools to streamline workflows, automate tasks, and continuously improve engineering processes.
Mentor, coach, and upskill engineers on AI/ML tooling, MLOps practices, and integration patterns.
Lead collaboration across Platform, Data, and Security teams, representing PAII priorities in architecture, planning, and governance forums.