Senior AI or ML Engineer - Remote

Role overview

Optum is seeking a Senior AI/ML Engineer for its Consumer Engineering team within the Chief Digital Office (CDO). The role focuses on designing and deploying scalable AI/ML models that enhance the consumer healthcare experience, working with cross-functional teams to build secure data pipelines and automated infrastructure at enterprise scale.

Responsibilities

• Execute tasks across the AI/ML software development life cycle (SDLC) for AI/ML tools and applications
• Design, develop, and deploy AI-powered solutions for complex business problems, emphasizing responsible AI
• Use enterprise-approved AI tools to streamline workflows and automate tasks
• Build clean, efficient, scalable code for tools/pipelines/applications in Python, Core Java, or Scala
• Automate infrastructure provisioning and DevOps using tools such as Terraform
• Review, debug, and optimize code for quality, security, and performance
• Perform validation, performance, and verification testing for deep learning and machine learning models
• Evaluate emerging AI/ML trends and research to inform solution design and innovation
• Document architectures and monitor deployed AI systems for reliability

Required qualifications

• Bachelor’s degree or 4+ years equivalent software engineering or data science experience
• 5+ years software development experience with proficiency in Python, Core Java, or Scala
• 3+ years designing, building, and deploying AI/ML models or pipelines into production
• 3+ years cloud platforms: Azure or AWS and Kubernetes container orchestration
• 2+ years data engineering experience (e.g., GraphQL, database design, data pipeline construction)
• 2+ years infrastructure automation using tools such as Terraform
• Experience using version control (e.g., GitHub) for team collaboration

Preferred qualifications

• Bachelor’s or Master’s degree in CS, Data Science, AI/ML, or related field
• Experience with large-scale datasets, data warehousing, and distributed query engines
• Experience implementing CI/CD pipelines for ML (MLOps)
• Knowledge of Generative AI, Large Language Models (LLMs), and prompt engineering best practices