Note: The job is a remote job and is open to candidates in USA. Optum is a global organization that delivers care aided by technology to help millions of people live healthier lives. The AI/ML Engineer will design, develop, and deploy responsible AI and machine learning solutions, including Generative AI, while contributing to prototypes, model integrations, APIs, cloud pipelines, and performance optimization across the healthcare ecosystem.
Responsibilities
- Design, develop, and deploy AI-powered solutions to address complex business challenges with an emphasis on responsible use of AI
- Implement and iterate on AI and machine learning solutions (including Generative AI) by building prototypes, integrating models into services, and improving quality based on evaluation results
- Use enterprise-approved AI tools to streamline engineering workflows, automate tasks, and drive continuous improvement
- Support proof-of-concept projects and model experiments, establishing performance baselines using clear metrics and standard tooling
- Contribute to training and inference pipelines using Databricks, PySpark, and cloud platforms (AWS, Azure, or Google Cloud Platform) under guidance from senior engineers
- Learn and apply Generative AI building blocks such as Retrieval-Augmented Generation (RAG) and prompt orchestration tools (e.g., LangChain)
- Contribute to building and testing REST APIs (e.g., FastAPI) and learn delivery fundamentals such as containerization (Docker) and application frameworks (e.g., Flask/Streamlit)
- Support performance and cost optimizations (e.g., caching, batching, quantization, or distillation) to enhance system efficiency
- Collaborate with cross-functional partners to understand business needs, ask clarifying questions, participate in code reviews, and maintain team standards for quality, safety, and trust
Skills
- Bachelor's degree in Computer Science, IT, Data Science, or a related field (or 4+ years of equivalent software engineering experience in lieu of degree)
- 2+ years of software engineering experience delivering well-tested applications and services (including co-ops, internships, academic, or personal projects)
- 1+ years of AI/ML engineering experience, including prototyping, evaluation, and supporting deployment/monitoring in collaboration with senior engineers
- 1+ years of hands-on experience with Python and SQL through coursework, internships, or professional projects
- 1+ years of experience with at least one major cloud platform (AWS, Azure, or Google Cloud Platform)
- Exposure to Generative AI building blocks (RAG, prompt orchestration tools like LangChain, and vector databases)
- Experience building and testing APIs (e.g., REST with FastAPI) and working with containers (Docker) or application frameworks (Flask/Streamlit)
- Familiarity with MLOps concepts (experimentation tracking, model packaging, deployment patterns, and monitoring basics)
- Exposure to Infrastructure as Code (IaC) tools such as Terraform or CloudFormation
- Awareness of data governance and access control concepts; familiarity with Databricks features like Delta Lake and Unity Catalog
- Exposure to big data technologies such as Spark (PySpark/SparkSQL) and streaming/messaging tools (e.g., Kafka/Hadoop)
- Basic understanding of data science fundamentals (statistics, probability, metrics, and data modeling) and performance optimization techniques (caching, batching, quantization, or distillation)
Benefits
- Flexibility to telecommute from anywhere within the U.S.
- Comprehensive benefits package
- Incentive and recognition programs
- Equity stock purchase
- 401k contribution
- Career development opportunities
Company Overview
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