Staff Machine Learning Engineer

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: • 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. 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. • 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 Qualifications: • Experience developing automated prompt optimization or prompt evaluation systems • Experience building model benchmarking frameworks or evaluation infras