Senior AI/ML Engineer for HealthTech (Remote)

Taleo; San Diego (CA); Remote; USD 120,000 - 215,000; Full time

Benefits offered by this job

Remote work flexibility

Comprehensive benefits package

Equity stock purchase

401k contribution

Job summary

UnitedHealth Group is seeking a seasoned ML Engineer to enable autonomous medical coding in a SaaS platform. You will collaborate with data scientists and software engineers on data extraction, training, and production deployment for millions of medical charts daily.

You’ll advance MLOps/LLMOps, design scalable architectures, and drive end-to-end ML solutions in a fast-paced environment with remote work flexibility across the U.S. Some in-office presence may apply for certain locations.

Qualifications

• BS or higher in CS/Engineering/Statistics or 4+ years of practical experience
• 5+ years of industry experience building and operating ML systems in production
• 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 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

Responsibilities

• 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

Skills

C# / Python

Azure

ML systems

MLOps

LLMOps

Data science

Communication

Education

Bachelor's degree or higher in CS/Engineering/Statistics

Tools

Docker

Kubernetes

MLflow

CI/CD for ML

Job description

UnitedHealth Group is seeking a seasoned ML Engineer to enable autonomous medical coding in a SaaS platform. You will collaborate with data scientists and software engineers on data extraction, training, and production deployment for millions of medical charts daily.

You’ll advance MLOps/LLMOps, design scalable architectures, and drive end-to-end ML solutions in a fast-paced environment with remote work flexibility across the U.S. Some in-office presence may apply for certain locations.