AI/ML Engineer

UnitedHealth Group•Minnetonka, MN

4d•$98,500 - $176,000•Remote

About The Position

As an AI/ML Engineer on Optum Technology’s technology team, you will design, build, and deploy artificial intelligence and machine learning capabilities to transform healthcare operations. You will develop scalable GenAI models, LLM applications, agentic frameworks, and Python inference APIs deployed on Kubernetes. The role uses modern developer tools and semantic search to deliver accessible AI solutions across enterprise healthcare data. The position is telecommutable from anywhere within the U.S., subject to UnitedHealth Group’s Telecommuter Policy.

Requirements

At least 4 years of software development, data engineering, or AI/ML experience.
At least 4 years of professional Python experience using core data science and machine learning libraries, such as scikit-learn or Databricks.
At least 3 years of commercial enterprise experience applying machine learning techniques, including supervised or unsupervised learning, time-series forecasting, or statistical analysis.
At least 2 years of production experience applying NLP (such as transformers or GPT) or LLMs (such as RAG, vector databases, or embeddings) with large-scale datasets.
At least 1 year of experience building, deploying, and maintaining RESTful APIs for machine learning model inference.

Nice To Haves

Bachelor's degree or equivalent experience.
Strong analytical, quantitative, problem-solving, and critical-thinking skills.
Strong written and verbal communication skills, including presenting detailed technical analyses to diverse technical and business stakeholders.
Experience with GenAI vision and speech models or multimodal architectures.
Healthcare data analytics experience, such as with claims, eligibility, or enrollment, and experience working in regulated compliance environments.
Hands-on experience with containerization and orchestration technologies such as Docker and Kubernetes.
Experience using AI-assisted developer and coding tools to accelerate software production and technical documentation.
Familiarity with agentic frameworks, Model Context Protocol (MCP), and Agent-to-Agent (A2A) architectures.

Responsibilities

Design, develop, and validate machine learning models using GenAI, including LLMs and agentic frameworks, as well as traditional ML techniques on cloud platforms.
Write and deploy scalable Python APIs for model inference on Kubernetes, including containerization and orchestration of agentic flows.
Implement and integrate semantic search to improve data accessibility and retrieval for analytics and business intelligence.
Design, develop, and deploy AI-powered solutions for complex business challenges, emphasizing responsible AI use.
Evaluate emerging technology trends and best practices to inform solution design, architecture, and strategic innovation.
Use enterprise-approved AI tools to streamline developer workflows, automate tasks, and improve continuous software delivery.
Use agentic coding and version-control tools, such as GitHub Copilot and Claude, for code creation, repository management, and technical collaboration.
Maintain coding standards, thorough documentation, and performance monitoring across deployed AI/ML pipelines.