Sr. AI/ML Engineer - Remote

UnitedHealth Group•Richardson, TX

7h•$120,100 - $214,500•Remote

About The Position

Optum Health Technology is seeking a Senior AI/ML Engineer with a data science background to build and scale AI-powered solutions that transform value-based care delivery. The role leads the design, development, statistical analysis, and enterprise deployment of machine learning models, generative AI architectures, predictive analytics, and intelligent automations to improve patient health outcomes and operational efficiency. The engineer works with software engineers, data scientists, data architects, product managers, and clinical leaders to translate clinical data into actionable intelligence, streamline healthcare workflows, support clinical decision-making, and deliver value across the care continuum. The position is remote from anywhere within the United States. Hires in the Minneapolis or Washington, D.C. area must work in the office at least four days per week. Remote employees must adhere to UnitedHealth Group’s Telecommuter Policy.

Requirements

At least 5 years of software engineering, machine learning engineering, or data science experience in a production enterprise environment.
At least 3 years of hands-on experience designing, statistically modeling, training, evaluating, and deploying machine learning or deep learning models in production.
At least 3 years of proficiency with Python and core AI/ML and data science libraries, such as PyTorch, TensorFlow, scikit-learn, Pandas, NumPy, and SciPy.
At least 2 years of experience with cloud platform infrastructure (AWS, Azure, or GCP) and cloud-native AI/ML/data services such as SageMaker, Azure ML, or Vertex AI.
At least 2 years of experience in statistical analysis, predictive modeling, hypothesis testing, and advanced data manipulation on complex datasets.
At least 2 years of experience implementing MLOps, CI/CD pipelines, containerization (Docker, Kubernetes), and model monitoring or governance frameworks.

Nice To Haves

A master’s or bachelor’s degree in Data Science, Computer Science, Statistics, Applied Mathematics, or a related quantitative field.
Experience with Large Language Models, generative AI architectures, prompt engineering, and Retrieval-Augmented Generation frameworks.
A proven track record of using modern AI coding tools and automation frameworks to accelerate software and data science delivery.
A background in healthcare technology, clinical data standards such as FHIR or HL7, or highly regulated data compliance environments such as HIPAA or HITRUST.
Experience with distributed data processing systems and analytics platforms such as Apache Spark, Databricks, or Snowflake.

Responsibilities

Design, develop, and deploy AI-powered solutions for complex healthcare challenges, emphasizing responsible and ethical AI use.
Perform exploratory data analysis, feature engineering, statistical modeling, and hypothesis testing on large-scale clinical and healthcare datasets.
Use enterprise-approved AI tools and frameworks to streamline engineering workflows, automate repetitive tasks, and improve processes.
Evaluate emerging AI/ML trends, foundational models, statistical techniques, and technical tools to inform architecture and innovation.
Build, optimize, and maintain production-grade machine learning pipelines and predictive models for preprocessing, training, evaluation, and monitoring.
Architect scalable microservices and APIs that integrate machine learning models and data science capabilities into enterprise applications and clinical workflows.
Collaborate with technical, data, and clinical teams to translate business objectives into robust, secure, and performant solutions.
Implement MLOps practices for continuous integration, automated model evaluation, governance, model tracking, and reliable enterprise-scale deployment.