Senior AI ML Engineer - Remote

UnitedHealth Group•Boston, MA

16h•Remote

About The Position

Optum Insight is improving the flow of health data and information to create a more connected system. We remove friction and drive alignment between care providers and payers, and ultimately consumers. Our deep expertise in the industry and innovative technology empower us to help organizations reduce costs while improving risk management, quality and revenue growth. Ready to help us deliver results that improve lives? Join us to start Caring. Connecting. Growing together. Optum is a global organization that delivers care, aided by technology, to help millions of people live healthier lives. The work you do with our team will directly improve health outcomes by connecting people with the care, benefits, data and resources they need to feel their best. Here, you will find a culture guided by diversity and inclusion, talented peers, comprehensive benefits, and career development opportunities. As a lead AI/ML Engineer at Optum AI, you’ll be designing and developing AI systems to improve patient care. About the AI Platform Team We often deliver the entire solution, from healthcare data ingest, generative agents and AI models deployment, data extraction, agent/model results and analytics, to the applications used for reviewing clinical data and AI results. Our current projects involve both leveraging and building cutting edge Generative AI and Agentic AI technologies from scratch. We have the data and resources to make an impact on a scale. When our solutions are deployed, they benefit millions of people. We are a globally distributed and diverse team with the shared passion to improve patient outcomes, improve healthcare operations, and streamline payments. We pay attention to the details to make sure we deliver quality, the first time. 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

Bachelor's degree in Computer Science or related field, or 4+ years of equivalent experience
4+ years of experience in Python programming
4+ years of hands-on experience in modern cloud infrastructure (AWS, Azure or Google. GCP is a plus)
4+ years of experience working with various AI/ML infrastructure, tools and platforms across the full stack of AI/ML technology
2+ years of experience in a team lead role
1+ years of experience leveraging Large Language Models (LLMs)
Proven track record of engaging with customers to design and deliver at least two complete AI products, from ideation to product release

Nice To Haves

Proven solid knowledge of CI/CD principles with hands‑on experience designing and operating multiple production‑grade pipelines
Proficient with GitHub and GitHub Actions, artifact and dependency management, containerization using Docker, and infrastructure‑as‑code using Terraform to enable reliable, repeatable, and secure deployments
Experience with the challenges of delivering and monitoring LLM based cloud systems into production
Experience in Healthcare
Proven solid communication skills with the ability to explain complex technical concepts to diverse audiences
Demonstrated bias for action
Demonstrated passion for innovation and staying current with emerging AI/ML trends

Responsibilities

Lead and contribute to the design and hands-on implementation of AI/ML platform that enables Optum to derive information from patient data in a scalable, reliable, and cost-effective manner
Partner with product managers, data scientists, prompt designers, engineers, and business stakeholders to translate business requirements into scalable AI systems
Leverage AI assisted tools for design, implementation, code reviews, and testing
Ensure the delivery of high-quality, maintainable, and efficient code and specifications. Lead by example to deliver product quality the first time
Drive architectural decisions and contribute to our long-term technical strategy for AI/ML systems
Own end‑to‑end delivery of platform and agent capabilities, from problem definition through design, implementation, modular packaging, deployment, and production monitoring
Partner with cross-functional teams to define scope, success criteria, and delivery milestones, then execute with solid engineering rigor through CI/CD, environment readiness, and quality gates to deliver on schedule without compromising reliability or maintainability
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
Be a trusted technical advisor to management, internal stakeholders, and customers
Mentor and lead other engineers to reach their potential