Principal Machine Learning Platform Engineer, Foundation AI

San Mateo, CA · San Mateo · USD 295,250-345,050 / year · 10+ years experience · Full-time · Onsite · Posted Oct 12, 2026

At a glance

The Principal Machine Learning Platform Engineer will own the ML platform as a product, designing and building infrastructure that powers billions of inferences daily.
This role focuses on creating durable APIs, SDKs, and tools that enable internal developers to train, evaluate, and deploy models efficiently.
The position requires a blend of product thinking, developer experience, and large-scale backend infrastructure engineering.

Define requirements, write RFDs, and ship APIs, SDKs, CLIs, and UIs for the ML platform.
Bootstrap and maintain core ML Platform components including the Serving Layer, Model Registry, Pipeline Orchestrator, and control planes.
Set technical strategy and oversee development of high-scale infrastructure systems with clear SLOs.
Design developer experiences using paved-road templates, golden paths, and opinionated defaults.
Instrument the platform to measure adoption, friction, reliability, and cost.
Partner with ML Engineering, Data Science, Infra/SRE, Security, and Finance teams to optimize performance and spend.
Propose and implement new platform tooling to improve time-to-production for ML engineers.
Stay abreast of industry trends in machine learning and infrastructure.
Mentor junior and senior engineers and lead design reviews.

10+ years of professional experience.
Extensive system design experience for scalable, reliable platforms.
Proficiency in API design and developer experience, including gRPC, REST APIs, SDKs, and CLIs.
Experience with infrastructure-as-code and automation.
Bachelor's degree in Computer Science, Computer Engineering, Data Science, or a similar technical field.
Strong written and verbal communication skills.

Hands-on ML experience.
Experience with the end-to-end ML model lifecycle such as model serving, training, model CI/CD, and GPU resources management.