AI/ML Engineer II - Remote

About the Company

Optum Tech develops healthcare technology solutions that help people live healthier lives and improve how the healthcare system operates. Its teams work across data analytics, artificial intelligence, cybersecurity, and other technology areas to address complex healthcare challenges.

Optum is part of UnitedHealth Group, whose mission is to help people live healthier lives and make the health system work better for everyone.

About the Role

Optum Tech is seeking an experienced Machine Learning Engineer to develop production-ready machine learning systems and integrate large language models into a SaaS platform for autonomous medical coding. You will collaborate with data scientists and software engineers to extract and prepare data, research and train models, and deploy scalable solutions capable of processing millions of medical charts daily.

This role focuses on building reliable ML systems, improving model performance, and applying modern MLOps and LLMOps practices. The position is remote within the United States, subject to the company's telecommuter policy. Employees based in the Minneapolis or Washington, D.C. areas must work from the office at least four days per week.

Key Responsibilities

• Develop and deploy production machine learning systems across problem definition, data discovery, feature engineering, training, evaluation, monitoring, and continuous improvement.
• Design robust ML architectures that support low-latency inference and high availability.
• Build and maintain reliable data and model pipelines using MLOps practices, including CI/CD for machine learning, model registries, experiment tracking, and automated retraining.
• Help define technical scope and break complex initiatives into actionable roadmaps, coordinating execution across cross-functional teams.
• Develop evaluation strategies using appropriate metrics, simulations, counterfactual analysis, and A/B testing.
• Measure model impact and maintain statistical rigor throughout development and deployment.
• Implement model observability and governance, including drift detection, performance monitoring, fairness assessments, and model documentation.
• Work with product, design, data, and platform teams to translate business objectives into machine learning solutions with measurable outcomes.
• Apply machine learning and LLM technologies to support autonomous medical coding within a scalable SaaS environment.

Required Qualifications

• A bachelor's degree or higher in Computer Science, Engineering, Statistics, or a related field, or at least 4 years of equivalent practical experience.
• At least 5 years of industry experience building and operating production machine learning systems, with demonstrated delivery of measurable results.
• At least 3 years of experience with C# or Python.
• At least 3 years of experience working with Microsoft Azure.
• At least 3 years of experience with supervised learning, feature engineering, evaluation methods, bias-variance trade-offs, and deep learning or gradient boosting.
• At least 3 years of MLOps experience, including ML CI/CD, containers, Kubernetes or serverless inference, model registries, reproducibility, and model monitoring.
• At least 1 year of LLMOps experience involving prompt engineering, retrieval-augmented generation, fine-tuning, evaluation, and safety guardrails.

Preferred Qualifications

• Experience in recommendations, ranking, time-series forecasting, optimization, or reinforcement learning.
• Contributions to open-source projects, research publications, or patents.
• Strong communication skills and product judgment, with the ability to translate business requirements into technical plans and explain trade-offs to non-ML stakeholders.
• Experience applying privacy, security, and responsible AI practices, including GDPR/CCPA considerations, personally identifiable information handling, and fairness.
• Strong foundations in machine learning and statistics, including supervised learning, feature engineering, model evaluation, and bias-variance trade-offs, with experience in deep learning or gradient boosting.

Compensation and Benefits

• The annual salary range for this full-time position is $120,100–$214,500.
• Compensation depends on factors such as local labor market conditions, education, work experience, certifications, and other relevant qualifications.
• Eligible employees may receive a comprehensive benefits package, incentive and recognition programs, an employee stock purchase program, and 401(k) contributions.
• Benefits and incentives are subject to eligibility requirements and applicable minimum wage laws.
• Work Environment This is a remote position available to candidates within the United States, subject to UnitedHealth Group's Telecommuter Policy.
• Candidates should be comfortable collaborating with cross-functional teams and developing production machine learning solutions in a fast-paced environment.
• Employees hired for locations in Minneapolis or Washington, D.C. are required to work in the office at least four days per week.

Equal Employment Opportunity

UnitedHealth Group is an Equal Employment Opportunity employer. Qualified applicants are considered without regard to race, national origin, religion, age, color, sex, sexual orientation, gender identity, disability, protected veteran status, or other characteristics protected by applicable law.

The company is committed to reducing barriers to healthcare, addressing health disparities, improving equitable access to care, and minimizing its environmental impact. UnitedHealth Group is a drug-free workplace, and candidates must pass a drug test before beginning employment.