MCG Health - Staff Machine Learning Engineer
Requirements
• 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. • 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 • Experience developing reusable ML engineering frameworks or standards adopted across multiple team • Strong technical communication and collaboration skills, with the ability to influence decisions through expertise rather than positional authority • Demonstrated ability to operate effectively in ambiguous, fast-moving environments while balancing technical rigor with delivery
Responsibilities
• 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. • 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, defining appropriate 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 the quality, efficiency, and scalability of ML experimentation and continuous improvement. • Provide technical guidance and mentorship to engineering and cross-functional partners, influencing outcomes through technical expertise and judgment without direct people-management responsibility.
Benefits
• Location: Seattle Preferred • 💻 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.
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