[Remote] Lead AI ML Engineer - Remote

Note: The job is a remote job and is open to candidates in USA. Optum is a global leader in health care innovation, developing advanced solutions to improve health systems and outcomes. The Lead AI/ML Engineer will design, build, and deploy AI and machine learning solutions while collaborating with cross-functional teams to drive innovation and operational excellence.

Responsibilities

• Architect, develop, and deploy scalable AI/ML platforms and full stack application solutions, spanning model training, inference, APIs, and user experiences
• Implement AI/ML computing infrastructures and application stacks using frameworks such as AWS Bedrock core/Google ADK, with orchestration using AWS AgentCore for multi agent workflows
• Design end to end pipelines covering data ingestion, feature processing, model serving, and observability
• Build and maintain production grade backend services and APIs using Java and Python
• Develop and integrate frontend and lightweight UI components (eg, dashboards, internal tools) to operationalize AI workflows and analytics
• Apply modern software engineering practices including CI/CD pipelines, containerization, and cloud native deployment
• Partner closely with data scientists, product managers, UX teams, and business stakeholders to translate complex business requirements into scalable AI and full stack solutions
• Act as a bridge between research, engineering, and product teams to ensure solutions are practical, performant, and maintainable
• Define and document architecture roadmaps, reference architectures, and standard operating procedures for AI/ML systems
• Ensure alignment with enterprise standards for reliability, security, fairness, transparency, and regulatory compliance
• Lead technical design reviews, guide architectural decisions, and oversee model evaluation, optimization, and deployment cycles
• Mentor junior and senior engineers, setting clear expectations for code quality, system design, and operational readiness
• Conduct applied research to advance capabilities in Generative AI, NLP, NLU, computer vision, and predictive modeling
• Stay current with emerging tools, architectures, and industry trends, and translate them into actionable engineering practices
• Lead disaster recovery and business continuity planning for AI and application infrastructure
• Monitor, tune, and continuously improve deployed models and services for performance, accuracy, scalability, and cost efficiency

Skills

• Bachelor's or Master's degree in Computer Science, Data Science, Engineering, or a related technical field
• 9+ years of professional software engineering experience, with demonstrated success designing and delivering high quality, commercial full stack applications in production environments
• 6+ years of hands on proficiency in Java, Python, SQL, and Linux shell scripting, with production experience in distributed systems
• 5+ years of AI/ML engineering experience, including deploying models at scale and leading or mentoring technical teams
• 4+ years of Solid cloud experience in various CSPs (especially AWS)
• 2+ years of applied AI/ML experience, including deep learning, NLP/NLU, semantic understanding, intent classification, ASR, predictive modeling, and time series analysis
• 2+ years of experience in MongoDB and MLOps
• Proven cloud experience with Google Cloud (Vertex AI) and working knowledge of AWS, including cloud native architectures, containerization, and orchestration
• Hands on experience with Hadoop ecosystems, and MLOps practices for model lifecycle management
• Experience integrating AI/ML models into end to end, user facing applications
• Solid understanding of API based architectures, distributed data systems, and scalable backend services
• Must be authorized to work in the United States without the need for current or future employer-sponsored visa sponsorship (e.g., H-1B, TN, F-1/OPT, CPT, or other employment-based visa status)
• Experience working in enterprise or regulated environments with governance and compliance requirements
• Data Science Foundations: Solid grounding in statistics, probability theory, optimization, simulation, and data modeling
• Communication & Influence: Ability to clearly present complex analytical and AI concepts to both technical and non technical audiences

Benefits

• A comprehensive benefits package
• Incentive and recognition programs
• Equity stock purchase
• 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.
• You'll enjoy the flexibility to work remotely rom anywhere within the U.S.
• 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.

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