Staff Machine Learning Engineer

MCG Health

. Design, build, and evolve ML engineering tooling for MCG’s AI-powered clinical solutions, including automated prompt tuning, content feedback loops, and model benchmarking .

Posted 11/5/2026full-timeRemote • Washington • United StatesLead💰 $154,000 - $216,000 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in designing and implementing production-quality machine learning systems and tooling, with a strong focus on collaboration across cross-functional teams. Capable of translating complex ML and clinical AI requirements into effective technical solutions while maintaining high standards of experimentation and continuous improvement.

Highest-signal resume keywords

Machine Learning EngineeringPython ProgrammingProduction-Quality Systems DesignTechnical CommunicationCollaboration with Cross-Functional Teams

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Machine Learning SystemsAutomated Prompt OptimizationModel Benchmarking FrameworksML OperationsExperimentation PlatformsReusable ML Engineering FrameworksTechnical Problem SolvingData Science EngineeringSoftware Engineering PracticesModel Observability

Soft Skills

Technical GuidanceMentorshipInfluencing DecisionsCollaboration SkillsAdaptability in Ambiguous Environments

Certifications & Qualifications

Bachelor’s Degree in Computer ScienceBachelor’s Degree in EngineeringBachelor’s Degree in Data Science

Industry Keywords

AI-Powered Clinical SolutionsML ExperimentationContinuous ImprovementTechnical AuthorityClinical AI

Tech Stack

Tools & technologies

Python

About the role

Key responsibilities & impact

Design, build, and evolve ML engineering tooling for MCG’s AI-powered clinical solutions, including automated prompt tuning, content feedback loops, and model benchmarking
Develop scalable experimentation and evaluation infrastructure for rapid, reproducible comparison and optimization of models, prompts, and AI approaches
Partner with Data Science, Clinical Prompt Engineering, Software Engineering, and Product teams to translate model improvement opportunities into reliable technical solutions
Translate ambiguous ML and clinical AI requirements into technical approaches, methodologies, interfaces, and implementation plans
Investigate complex ML engineering problems and develop practical solutions when established approaches or frameworks are insufficient
Establish reusable engineering patterns, standards, and best practices that improve ML experimentation and continuous improvement
Provide technical guidance and mentorship to engineering and cross-functional partners without direct people-management responsibility
Operate as a technical authority influencing how MCG evaluates, improves, and operationalizes AI-enabled clinical solutions

Requirements

What you’ll need

Bachelor’s degree in Computer Science, Engineering, Data Science, or a related technical field, or equivalent practical experience
At least 6 years of relevant professional experience in machine learning engineering, software engineering, data science engineering, or a closely related technical discipline
Experience designing and implementing production-quality machine learning systems, tooling, or infrastructure is required
Experience with Python and modern software engineering practices
Demonstrated ability to independently solve complex technical problems and determine effective approaches within an ambiguous problem space
Demonstrated experience collaborating with Data Science, Engineering, Product, or other cross-functional technical teams
Preferred: Experience developing automated prompt optimization or prompt evaluation systems
Preferred: Experience building model benchmarking frameworks or evaluation infrastructure for large language models
Preferred: Experience developing feedback loops that incorporate human or expert evaluation into ML systems
Preferred: Experience with model observability, experimentation platforms, or ML operations
Preferred: Experience developing reusable ML engineering frameworks or standards adopted across multiple team
Preferred: Strong technical communication and collaboration skills, with the ability to influence decisions through expertise rather than positional authority
Preferred: Demonstrated ability to operate effectively in ambiguous, fast-moving environments while balancing technical rigor with delivery

Benefits

Comp & perks

Bonus Eligible
Remote Work/Hybrid Work
Travel expected 1–3 times per year for company-sponsored events
Medical, dental, vision, life, and disability insurance
401K retirement plan
Flexible spending and health savings account
15 days of paid time off + additional front-loaded personal days
14 company-recognized holidays
Paid volunteer days
Up to 8 weeks of paid parental leave + 10 weeks of paid bonding leave
LGBTQ+ Health Services
Pet insurance
Accommodations for individuals requiring support