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Lead AI​/ML Engineer Remote Nationwide or Office-Based in MN​/DC

Remote / Online - Candidates ideally in
Eden Prairie, Hennepin County, Minnesota, 55346, USA
Listing for: UnitedHealth Group
Remote/Work from Home position
Listed on 2026-10-16
Job specializations:
  • Software Development
    AI Engineer (Applied/Software), Machine Learning/ ML Engineer
Salary/Wage Range or Industry Benchmark: 145500 - 249500 USD Yearly USD 145500.00 249500.00 YEAR
Job Description & How to Apply Below
Job d:

Location:

Eden Prairie, Minnesota, United States Salary: $145,500 - $249,500/year

Job Area:
Technology Company:
United Health Group 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 to start Caring. Connecting. Growing together. You'll enjoy the flexibility to work remotely
* from anywhere within the U.S. as you take on some tough challenges. For all hires in the Minneapolis or Washington, D.C. area, you will be required to work in the office a minimum of four days per week.

Primary Responsibilities:

Lead the design, development, and delivery of enterprise AI/ML solutions that address complex business and technology needs

Develop and operationalize AI/ML capabilities, including machine learning models, generative AI applications, analytics solutions, and intelligent automation

Provide technical leadership for solution design, architecture decisions, engineering practices, and delivery approaches across AI/ML initiatives

Apply appropriate AI, machine learning, data, and software engineering techniques to build scalable, reliable, and maintainable solutions

Support modern AI/ML delivery practices, including experimentation, deployment, monitoring, governance, and continuous improvement

Help ensure AI/ML solutions are production-ready, observable, secure, compliant, and aligned with enterprise standards

Work with stakeholders to define success measures, evaluate outcomes, and ensure AI/ML solutions deliver measurable business value

Evaluate and improve AI/ML solutions for performance, quality, scalability, maintainability, and cost-effectiveness

Collaborate on data, feature, and retrieval pipelines that support AI/ML development, evaluation, deployment, and monitoring

Partner with product, business, data, platform, security, compliance, operations, and engineering teams to deliver AI/ML capabilities in enterprise environments

Promote reusable patterns, shared components, engineering standards, documentation, and responsible AI practices across teams

Apply responsible AI, risk management, privacy, security, and compliance considerations throughout the AI/ML lifecycle

Identify technical risks, communicate trade-offs, and guide practical mitigation approaches for AI/ML solutions

Select appropriate techniques and tools based on business needs, technical feasibility, quality expectations, and operational considerations

Balance innovation with practical delivery by choosing reliable, explainable, maintainable, and cost-effective approaches

Mentor engineers, review technical work, share knowledge, and help raise engineering quality across AI/ML initiatives

Communicate technical concepts, recommendations, risks, and outcomes clearly to technical and non-technical audiences AI/ML Engineers design, build, and support software solutions that apply artificial intelligence, machine learning, analytics, and automation to solve business problems. Work may include model development, generative AI, data-driven applications, evaluation, deployment, monitoring, and continuous improvement. This role emphasizes sound engineering practices, collaboration, responsible AI, and translating business needs into scalable and reliable technology solutions

Reviews architecture, design, code, model outputs, evaluation results, and production readiness artifacts created by others

Develops innovative and reusable approaches that accelerate enterprise…
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