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

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.

The Platform, AI & Integration (PAII) team leads the design, delivery, and enterprise integration of AI/ML capabilities across our Cloud Platform. In this role, you will serve as a primary technical and people leader, driving the architecture, engineering standards, and deployment of machine learning models, intelligent services, and automation frameworks into core platform operations. Working at the intersection of cloud infrastructure, advanced data pipelines, and scalable artificial intelligence, you will guide an engineering team focused on creating robust, secure, and reliable AI solutions that transform how our platform operates at enterprise scale.

Primary Responsibilities:

• Provide technical and people leadership for the Platform, AI & Integration (PAII) engineering team, establishing engineering standards, best practices, and architectural direction
• Design, develop, and deploy AI-powered solutions to address complex business challenges with an emphasis on responsible use of AI
• Own end-to-end AI/ML model development, validation, and production deployment, ensuring intelligent services and automation frameworks are embedded securely and reliably into core platform operations
• Integrate AI/ML capabilities with core cloud platform services, infrastructure components, and modern data pipelines
• Drive the platform AI roadmap, architecture decisions, and robust MLOps practices to sustain delivery momentum 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 drive continuous improvement across engineering processes
• Mentor, coach, and upskill engineers on AI/ML tooling, MLOps practices, and integration patterns to foster team growth
• Lead cross-functional collaboration across Platform, Data, and Security teams, representing PAII priorities in architecture, planning, and governance forums

You'll be rewarded and recognized for your performance in an environment that will challenge you and give you clear direction on what it takes to succeed in your role as well as provide development for other roles you may be interested in.

Required Qualifications:

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

Preferred Qualifications:

• 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 within 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 (e.g., Apache Kafka)
• Demonstrated ability to manage stakeholders and convey complex technical concepts to cross-functional business partners

Pay is based on several factors including but not limited to local labor markets, education, work experience, certifications, etc. In addition to your salary, we offer benefits such as, a comprehensive benefits package, incentive and recognition programs, equity stock purchase and 401k contribution (all benefits are subject to eligibility requirements). No matter where or when you begin a career with us, you'll find a far-reaching choice of benefits and incentives. The salary for this role will range from $145,500 - $249,500 annually based on full-time employment. We comply with all minimum wage laws as applicable.

At UnitedHealth Group, our mission is to help people live healthier lives and help make the health system work better for everyone. Together, we are shaping the future of healthcare by harnessing technology and innovation to make care simpler to navigate, more affordable and more connected for the people we serve. We are committed to creating an inclusive workplace where everyone feels welcomed, valued, heard and respected, empowering people to bring their authentic selves to work and strengthening our collective impact through diverse talents, backgrounds, experiences and perspectives.

UnitedHealth Group and its affiliated brands are an Equal Employment Opportunity employer under applicable law and qualified applicants will receive consideration for employment without regard to race, national origin, religion, age, color, sex, sexual orientation, gender identity, disability, or protected veteran status, or any other characteristic protected by local, state, or federal laws, rules, or regulations.

UnitedHealth Group and its affiliated brands are a drug-free workplace. Candidates are required to pass a drug test before beginning employment.

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