> Markdown version of [/jobs/ext/3567081-sr-ai-ml-engineer-remote](https://www.wearedevelopers.com/jobs/ext/3567081-sr-ai-ml-engineer-remote). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Sr. AI/ML Engineer - Remote - **Company:** Optum, Inc - **Location:** Eden Prairie, MN, United States (Remote available) - **Experience:** Expert - **Salary:** $120,100.0 - $214,500.0 - **Contract:** Permanent contract - **Skills:** Application Programming Interfaces (APIs), Artificial Intelligence, Amazon Web Services, Business Analytics Applications, Data Analysis, Microsoft Azure, Big Data, Clinical Data Repository, Cloud Engineering, Continuous Integration, Data as a Services, Distributed Computing Environment, Statistical Hypothesis Testing, Python (Programming Language), Machine Learning, NumPy, Tensorflow, Azure Machine Learning, SciPy, Software Engineering, Data Processing, Enterprise Software Applications, Cloud Platform System, Feature Engineering, Pytorch, Fast Healthcare Interoperability Resources, Large Language Models, Snowflake, Prompt Engineering, Apache Spark, Deep Learning, Model Validation, Generative AI, Pandas, Containerization, Scikit Learn, Kubernetes, Information Technology, Health Level Seven International, Machine Learning Operations, Docker, Databricks, Microservices - **Published:** October 3, 2026 - **Apply:** https://arc.dev/remote-jobs/j/redirect/pou641y5hl ## About the Role * 5+ years of software engineering, machine learning engineering, or data science experience in a production enterprise environment * 3+ years of hands-on experience designing, statistical modeling, training, evaluating, and deploying machine learning or deep learning models in production * 3+ years of proficiency with Python and core AI/ML and data science libraries (e.g., PyTorch, TensorFlow, scikit-learn, Pandas, NumPy, SciPy) * 2+ years of experience with cloud platform infrastructure (AWS, Azure, or GCP) and cloud-native AI/ML/data services (e.g., SageMaker, Azure ML, Vertex AI) * 2+ years of experience in statistical analysis, predictive modeling, hypothesis testing, and advanced data manipulation on complex datasets * 2+ years of experience implementing MLOps, CI/CD pipelines, containerization (Docker, Kubernetes), and model monitoring/governance frameworks, * Master's or Bachelor's degree in Data Science, Computer Science, Statistics, Applied Mathematics, or a related quantitative field * Experience working with Large Language Models (LLMs), Generative AI architectures, prompt engineering, and Retrieval-Augmented Generation (RAG) frameworks * Experience with distributed data processing systems and analytics platforms such as Apache Spark, Databricks, or Snowflake * Background in healthcare technology, clinical data standards (FHIR, HL7), or working within highly regulated data compliance environments (HIPAA, HITRUST) * Proven track record of leveraging modern AI coding tools and automation frameworks to accelerate software and data science delivery * All employees working remotely will be required to adhere to UnitedHealth Group's Telecommuter Policy. ## Description * Design, develop, and deploy AI-powered solutions to address complex healthcare challenges with an emphasis on the responsible and ethical use of AI * Perform exploratory data analysis (EDA), feature engineering, statistical modeling, and hypothesis testing on large-scale clinical and healthcare datasets * Leverage enterprise-approved AI tools and frameworks to streamline engineering workflows, automate repetitive tasks, and drive continuous process improvement * Evaluate emerging AI/ML trends, foundational models, statistical techniques, and technical tools to inform architectural solution design and strategic innovation * Build, optimize, and maintain production-grade machine learning pipelines and predictive models for data preprocessing, model training, evaluation, and monitoring * Architect scalable microservices and APIs to integrate machine learning models and data science capabilities seamlessly into enterprise applications and clinical workflows * Collaborate with cross-functional technical, data, and clinical teams to translate high-level business objectives into robust, secure, and performant solutions * Implement MLOps best practices to ensure continuous integration, automated model evaluation, governance, model tracking, and reliable deployment at enterprise scale You'll be rewarded and recognized for your performance in an environment that will challenge you and give you clear direction on what it takes to succeed in your role as well as provide development for other roles you may be interested in. ## Related Videos - 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