Time since we first saw it
Day 1
Early. Similar jobs usually come down between day 6 and day 71.
From 4,626 similar postings that came down. Coming down is not always a hire.
Seattle Preferred
Actively hiring, first seen by us 1 day agoDemonstrated ability to operate effectively in ambiguous, fast-moving environments while balancing technical rigor with delivery Pay Range: $154,000 - $216,000 Other compensation: Bonus EligibleRead the full posting
Listed location: RemoteRead the full posting
Design and build ML tooling for automated prompt tuning and content feedback loops
Build scalable experimentation and evaluation infrastructure for comparing models and prompts
Turn ambiguous clinical AI requirements into technical approaches and implementation plans
Partner with data science, software, and product teams on model improvement solutions
Set reusable engineering patterns and standards for ML experimentation
Design, build, and evolve ML engineering tooling that accelerates continuous improvement of MCG’s AI-powered clinical solutions, including automated prompt tuning, content feedback loops, and model benchmarking
Develop scalable experimentation and evaluation infrastructure that enables rapid, reproducible comparison and optimization of models, prompts, and AI approaches.
Translate ambiguous ML and clinical AI requirements into technical approaches, defining appropriate methodologies, interfaces, and implementation plans.
Partner with Data Science, Clinical Prompt Engineering, Software Engineering, and Product teams to translate model improvement opportunities into reliable technical solutions.
Establish reusable engineering patterns, standards, and best practices that improve the quality, efficiency, and scalability of ML experimentation and continuous improvement.
Experience developing automated prompt optimization or prompt evaluation systems
Experience building model benchmarking frameworks or evaluation infrastructure for large language models
Experience developing feedback loops that incorporate human or expert evaluation into ML systems
Experience with model observability, experimentation platforms, or ML operations
What We're Looking For: - 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.
Actively hiringFirst seen by us 1 day ago, still listed, and not a repost of an earlier posting.
These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.
Day 1
Early. Similar jobs usually come down between day 6 and day 71.
From 4,626 similar postings that came down. Coming down is not always a hire.
3 open jobs
Open jobs by the week we first saw them, last 12 weeks.
Hiring recordAdd your resume and we’ll mark which of these tools you already use, and point out anything in the posting that could rule you out.
- 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.
Complete your application on job-boards.greenhouse.io. The employer’s form will show what is required.
Already applied? Track this application
New ML Engineer postings at the employers we follow are up 12% over the last 5 weeks compared with the 5 before.
Each bar is one week of new postings. The darkest bars are the last 5 weeks.
Counted from the hiring pages we’ve followed for at least five weeks, so employers we add don’t look like growth. Updated weekly.
We file this job under ML Engineer, by the work the posting describes.
ML engineers put machine learning models into products. They write the code that trains, ships, serves and monitors models so a recommendation or prediction works for real users.
Postings ask for strong Python and software engineering, a framework such as PyTorch, cloud services, and more and more often experience with large language models.
A data scientist often works out which model to build; an ML engineer makes it run reliably in production.
The government has no code for ML engineers, so these figures are for the closest group, computer and information research scientists.
Source: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics (May 2025) and Employment Projections (2025 to 2035). Occupation code 15-1221.
At MCG, we lead the healthcare community to deliver patient-focused care. We have a mission-driven team of talented physicians and technical experts developing our evidence-based content and innovating our products to accelerate improvements in healthcare. If you are driven to enhance the US healthcare system, MCG is eager to have you join our team. We cultivate a work environment that nurtures personal and professional growth, and this is a thrilling time to become a part of our organization. With dynamic roles that offer meaningful impact, you'll be able to fully realize your potential. Plus, you'll enjoy world-class benefits and the security, stability, and resources of our parent company, Hearst, with over 100 years of experience.
The Staff Machine Learning Engineer is a senior individual contributor responsible for building and evolving the machine learning engineering capabilities that enable continuous improvement of MCG’s AI-powered clinical solutions. The role focuses on developing tooling and infrastructure for automated prompt tuning, content feedback loops, model benchmarking, and related ML experimentation and evaluation capabilities. Working with Data Scientists, Clinicians, Software Engineers, and Product, this role translates model-quality and operational improvement opportunities into scalable technical solutions. The Staff ML Engineer operates with significant independence, serves as a technical authority within ML engineering, and influences how MCG evaluates, improves, and operationalizes AI-enabled clinical solutions.
You Will:
What We're Looking For:
Preferred Qualifications:
Pay Range: $154,000 - $216,000
Other compensation: Bonus Eligible
Location: Seattle Preferred
Perks & Benefits:
💻 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
📣 Check out more of our benefits here: https://www.mcg.com/about/careers/benefits/
All roles at MCG are expected to engage in occasional travel to participate in team or company-sponsored events for the purposes of connection and collaboration.
It is unlawful in Massachusetts to require or administer a lie detector test as a condition of employment or continued employment. An employer who violates this law shall be subject to criminal penalties and civil liability.
Note on interviews: We may use AI tools to audio-record and transcribe interviews for note-taking purposes. These are used only by our hiring team and do not make decisions on their own. Let us know if you prefer an alternative.
MCG is a leading healthcare organization dedicated to patient-focused care. We value our employees' unique differences and are an Equal Employment Opportunity (EEO) employer. Our diverse workforce helps us achieve our goal of providing the right care to everyone. We welcome all qualified applicants without regard to race, religion, nationality, gender, sexual orientation, gender identity, age, marital status, veteran status, disability, pregnancy, parental status, genetic information, or political affiliation. We are committed to improving equity in healthcare and believe that a diverse workplace fosters curiosity, innovation, and business success. We are happy to provide accommodations for individuals. Please let us know if you require any support.
Selected passages from the saved posting. Check the full description for conditions and exceptions.
Demonstrated ability to operate effectively in ambiguous, fast-moving environments while balancing technical rigor with delivery Pay Range: $154,000 - $216,000 Other compensation: Bonus Eligible
Remote
Perks & Benefits: 💻 Remote Work/Hybrid Work ✈️ Travel expected 1–3 times per year for company-sponsored events
No clear work-authorization passage found. Eligibility is unconfirmed.