Senior AI​/ML Engineer - Remote

Improve the lives of others while Caring. Connecting. Growing together.

Optum Tech is a global leader in health care innovation. Our teams develop cutting-edge solutions that help people live healthier lives and help make the health system work better for everyone. From advanced data analytics and AI to cybersecurity, we use innovative approaches to solve some of health care’s most complex challenges. Your contributions here have the potential to change lives.

Ready to build the next breakthrough? Join us to start Caring. Connecting. Growing together.

This role will enable autonomous medical coding in a SaaS platform by integrating machine learning and LLMs. Working closely with data scientists and software engineers through data extraction, research, training, and deployment to create a scalable production solution that can handle millions of medical charts daily. You will work with cutting edge models, LLM, software, and tools in a fast-paced environment.

You’ll enjoy the flexibility to work remotely
* from anywhere within the U.S. as you take on some tough challenges.

For all hires in the Minneapolis or Washington, D.C. area, you will be required to work in the office a minimum of four days per week.

• Ship production ML systems end-to-end: problem framing, data discovery, feature engineering, training, evaluation, deployment, monitoring, and iteration
• Design robust ML system architectures with low-latency inference and high availability
• Build and maintain reliable data and model pipelines using modern MLOps practices (CI/CD for ML, model registries, experiment tracking, automated retraining)
• Contribute to technical scoping and break down complex initiatives into executable roadmaps; drive execution across cross-functional partners
• Establish evaluation strategies: metrics, simulation, counterfactuals, and A/B tests; quantify impact and ensure statistical rigor
• Implement model observability and governance: drift detection, performance monitoring, fairness/bias assessments, and model documentation
• Collaborate closely with product, design, data, and platform teams to translate product goals into ML opportunities and measurable outcomes

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.

• Bachelor of Science or higher in Computer Science, Engineering, Statistics, or related field, or 4+ years of equivalent practical experience
• 5+ years of industry experience building and operating ML systems in production (or equivalent depth), with a track record of shipped impact
• 3+ years of experience in C# or Python
• 3+ years of Azure experience
• 3+ years of experience in supervised learning, feature engineering, evaluation methodology, bias/variance; deep learning and/or gradient boosting
• 3+ years of MLOps expertise including CI/CD for ML, containers, Kubernetes/serverless inference, model registries, reproducibility, and model monitoring
• 1+ years of experience with LLMOps including prompt engineering, retrieval-augmented generation, fine-tuning, evaluation, and safety/guardrails

• Domain experience in recommendations, ranking, time-series forecasting, optimization, or reinforcement learning
• Open-source contributions, publications, or patents experience
• MLOps expertise including CI/CD for ML, containers, Kubernetes, model registries, reproducibility, and model monitoring
• Demonstrated excellent communication and product sense; able to translate business needs into technical plans and explain tradeoffs to non-ML stakeholders
• Proven privacy, security, and responsible AI…