Principal Machine Learning Architect

MCG Health•Seattle, WA

4d•Hybrid

About The Position

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. MCG develops evidence-based guidelines that help patients get the right care in a variety of healthcare settings. The data science team at MCG combines AI with expert knowledge from our editors and guidelines to increase the efficiency and accuracy of our users’ documentation workflows. We have years of experience applying NLP to the clinical domain and are expanding the boundary of what can be done with agentic workflows in a reliable, explainable way. As a Principal ML Architect in MCG’s Data Science team, you will shape how our agent-based products move from early concepts to scalable solutions. You will partner with Product Managers, Software Engineers, Data Scientists, clinical partners, and customers to turn emerging needs into practical architectures, prototypes, and clear paths to delivery. This role combines technical direction with hands-on discovery and customer engagement, helping demonstrate the value of MCG’s agentic offerings and making adoption straightforward.

Requirements

At least 10+ years of experience in a ML Engineer role or a related field.
Demonstrated experience designing and shipping large-scale AI solutions with a focus on reliability and scalability.
Strong architecture judgment, including the ability to anticipate future needs and make sound long-term design decisions.
Experience working with early-stage customers to explore needs, shape requirements, and adapt solutions as new information emerges.
Ability to work through ambiguity and create a practical technical direction and execution plan from incomplete requirements.
Experience partnering across Product, Software Engineering, Data Science, clinical teams, and customer stakeholders.
Excellent written and verbal communication skills, including the ability to explain complex architecture choices clearly.

Nice To Haves

Experience with deep learning, natural language processing, or related AI methods.
Experience working in healthcare or with medical data.

Responsibilities

Lead technical discovery with Product Managers and customers, translating emerging needs and workflows into end-to-end architectures for AI features.
Set architectural direction for agent-based solutions, balancing near-term customer needs with scalable designs that can support future capabilities.
Build prototypes and proof-of-concept experiences to test feasibility, demonstrate value, and gather feedback from clinical personnel and customers.
Work directly with early-stage customers to understand their environments, identify adoption barriers, and shape requirements as solutions evolve.
Partner with Software Engineers and Data Scientists to move solutions from concept and prototype into reliable, scalable products.
Make architectural tradeoffs visible, identify risks early, and turn ambiguity into clear technical recommendations and execution plans.
Communicate architecture decisions, constraints, and opportunities clearly across technical, clinical, product, and customer audiences.