Lead AI/ML Engineer - Remote

UnitedHealth Group • San Diego, CA

1d • Remote

About The Position

Optum Insight is improving the flow of health data and information to create a more connected system. We remove friction and drive alignment between care providers and payers, and ultimately consumers. Our deep expertise in the industry and innovative technology empower us to help organizations reduce costs while improving risk management, quality and revenue growth. Ready to help us deliver results that improve lives? Join us to start Caring. Connecting. Growing together.
Lead the autonomous medical coding enablement 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 be responsible for architecture decisions, code reviews, and coordinating across teams. 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.
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.

Requirements

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

Nice To Haves

• Domain experience in recommendations/ranking, time-series forecasting, anomaly detection, optimization, or reinforcement learning
• Privacy, security, and responsible AI practices (GDPR/CCPA, PII handling, fairness)
• Open-source contributions, publications, or patents; prior experience mentoring or tech leading small teams
• Excellent communication and product sense; able to scope ambiguous problems and align stakeholders
• Open-source contributions, publications, or patents; prior experience mentoring or tech leading small teams
• Data engineering for ML: ETL/ELT, SQL, distributed processing (e.g., Spark), and feature pipelines
• Experimentation: A/B testing design/analysis, guardrail metrics, basic causal inference

Responsibilities

• Lead end-to-end ML projects: problem definition, data strategy, feature engineering, modeling, evaluation, deployment, and monitoring
• Architect scalable training and inference systems with strong SLAs, observability, and cost controls
• Establish experimentation rigor: offline evaluation, A/B testing, guardrails, power analysis, and causal insights
• Drive MLOps excellence: CI/CD for ML, reproducible pipelines, model registry and governance, automated retraining, drift/quality monitoring
• Collaborate with product and design to translate ambiguous goals into measurable ML problems; define success metrics and attribution
• Mentor and unblock engineers; conduct design and code reviews; set patterns for reliability, documentation, and testing
• Partner with data engineering on feature pipelines, data contracts, and online/offline parity; champion data quality
• Communicate tradeoffs and results to technical and non-technical stakeholders; influence roadmap and prioritization
• Optional focus areas depending on interest and business needs: LLM applications (RAG, fine-tuning, evaluation/guardrails), recommendations/ranking, anomaly detection, forecasting

Benefits

• In addition to your salary, we offer benefits such as, a comprehensive benefits package, incentive and recognition programs, equity stock purchase and 401k contribution (all benefits are subject to eligibility requirements).
• No matter where or when you begin a career with us, you’ll find a far-reaching choice of benefits and incentives.

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level
• Number of Employees: 5,001-10,000 employees