Lead AI/ML Engineer - Remote

UnitedHealth Group•Eden Prairie, MN

3d•Remote

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 to start Caring. Connecting. Growing together. Optum Insight partners with payers, providers, governments and life sciences companies to simplify and enhance clinical, administrative and financial processes through software-enabled services and analytics, while advancing value-based care. Our differentiated products, technology insights, clinical expertise and analytics support the entire health system - ultimately delivering better experiences for consumers. Optum Insight Technology and Engineering is a critical function in Optum Insight driving the innovation and value we provide our customers and partners. This team is focused on products, solutions, platform / enabling capability development, product development lifecycle, engineering excellence and connectivity to Optum Technology. The Clinical Decision Support (CDS) Engineering team, a unit within the Optum Insight Technology organization is responsible for building commercial products helping payers and providers with administrative and clinician focused CDS solutions. We are seeking a lead AI/ML engineer who can bring deep expertise across the full development lifecycle of machine learning and generative AI-based solutions from design to development to MLOps. CDS is an area that truly touches payers, providers, as well as members and one where you can have a huge impact on improving the healthcare system for everyone. 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.

Requirements

Bachelors degree in Computer Science or related major
4+ years of experience working with various AI/ML infrastructure, tools and platforms across the full stack of AI/ML technology including experience with the full development lifecycle from problem definition to MLOps
4+ years of experience working with Python with solid CS fundamentals and expertise in processing large datasets
4+ years of working experience in GCP, Azure or AWS platforms. (Azure is preferred)
1+ years of experience building AI Agents and solutions leveraging LLMs

Nice To Haves

Proven track record of leading technical projects from start to finish working with a cross functional team
Experience with AI/ML in healthcare domain
Proven solid communication skills with the ability to explain complex technical concepts to diverse audiences
Demonstrated bias for Action
Proven passion for innovation and staying current with emerging AI/ML trends, including GenAI and LLMs

Responsibilities

Design, develop, and deploy AI-powered solutions, translating business needs into scalable applications that enhance products, workflows and decision-making
Partner with product managers, data scientists, platform engineers, and business stakeholders to translate business requirements into scalable machine learning systems and ensure alignment across engineering, product, and operations teams
Champion best practices in software engineering, including code reviews, testing, CI/CD, and observability. Drive architectural decisions and contribute to long-term technical strategy for AI/ML systems
Own the full lifecycle of AI/ML initiatives-from problem definition and data exploration to model development, deployment, and monitoring. Define project scope, success metrics, and timelines in collaboration with cross-functional teams and ensure timely delivery of high-quality solutions by managing technical execution, risk mitigation, and stakeholder communication
Lead other ML Engineers in the team you'll collaborate with to code and develop software that deploys machine learning models, agents and prompts into production environments. This includes ensuring scalability, reliability and performance of deployed models.
Mentor and guide junior engineers and peers, fostering a culture of continuous learning, technical rigor, and ownership
Stay ahead of the curve on emerging AI/ML technologies, tools, and research, and evaluate their applicability to business problems. Embrace and promote a culture of innovation through rapid iteration, experimentation and data driven decision-making