[Remote] AI/ML Engineer

Note: The job is a remote job and is open to candidates in USA. Optum is a global organization that uses technology to help people live healthier lives and improve healthcare outcomes. The AI/ML Engineer will design, develop, and deploy scalable artificial intelligence and machine learning solutions, including GenAI models, LLM applications, agentic frameworks, and Python inference APIs on Kubernetes. The role focuses on delivering responsible, data-driven solutions across enterprise healthcare data and improving software delivery workflows.

Responsibilities

• Design, develop, and validate machine learning models using GenAI (LLMs, agentic frameworks) and traditional ML techniques on cloud platforms
• Write and deploy scalable Python APIs for model inference running on Kubernetes, ensuring efficient containerization and orchestration of agentic flows
• Develop and optimize Python-based analytical and machine learning solutions, leveraging libraries such as Pandas, NumPy, Scikit-learn, and Databricks to perform data analysis, build predictive models, and generate actionable business insights from large-scale datasets
• Design, develop, and deploy AI-powered solutions to address complex business challenges with an emphasis on responsible use of AI
• Evaluate emerging technology trends and best practices to inform solution design, architecture, and strategic innovation
• Leverage enterprise-approved AI tools to streamline developer workflows, automate tasks, and drive continuous software delivery improvement
• Utilize agentic coding and version control tools (e.g., GitHub Copilot, Claude) for efficient code creation, repository management, and technical collaboration
• Maintain rigorous coding standards, thorough documentation, and effective performance monitoring across all deployed AI/ML pipelines
• Design, develop, and deploy AI-powered solutions to address complex business challenges with emphasis on responsible use of AI

Skills

• 4+ years of experience in software development, machine learning, data science, analytics, or AI/ML engineering
• 4+ years of professional experience in Python using core data science, analytics, and machine learning libraries (e.g., Pandas, NumPy, Scikit-learn, Databricks)
• 4+ years of advanced SQL experience, including complex query development, data analysis, performance optimization, data validation, and deriving business insights from large-scale datasets
• 3+ years of experience applying machine learning techniques in enterprise environments, including supervised learning, unsupervised learning, statistical modeling, feature engineering, and model evaluation
• 2+ years of experience developing and deploying NLP or Generative AI solutions, including Transformers, GPT models, Retrieval-Augmented Generation (RAG), vector databases, embeddings, and prompt engineering in production environments
• 1+ years of experience building, deploying, and maintaining RESTful APIs for machine learning or Generative AI model inference
• Bachelor's degree or equivalent experience
• Strong analytical, quantitative, problem-solving, and critical thinking skills
• Strong written and verbal communication skills, including the ability to present detailed technical analyses to diverse technical and business stakeholders
• Experience with vision and speech models in GenAI (multimodal architectures)
• Background in healthcare data analytics (e.g., claims, eligibility, enrollment) and working within regulated compliance environments
• Hands-on experience with containerization and container orchestration technologies such as Docker and Kubernetes
• Experience utilizing AI-assisted developer and coding tools to accelerate software production and technical documentation
• Demonstrated familiarity with agentic frameworks, Model Context Protocol (MCP), and Agent-to-Agent (A2A) architectures
• Strong analytical and problem-solving skills with the ability to translate complex business problems into data-driven solutions and actionable insights
• Experience working with large structured and unstructured datasets, performing exploratory data analysis, data quality assessments, and root-cause investigations

Benefits

• Flexibility to telecommute from anywhere within the U.S.
• A comprehensive benefits package
• Incentive and recognition programs
• Equity stock purchase
• 401k contribution
• Career development opportunities

Company Overview

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