Senior Machine Learning Platform Engineer, Foundation AI

San Mateo, CA · San Mateo · USD 243,290-312,970 / year · 7+ years experience · Full-time · Onsite · Posted Oct 6, 2026

At a glance

ML Platform powers hundreds of use cases and billions of inferences per day across Discovery, Safety, Economy, and Creation.
This role blends product thinking, developer experience, backend engineering, and infrastructure at scale to build a scalable, reliable ML platform for all of Roblox.

Own platform as a product and set direction end to end: Define requirements, write RFDs, and ship APIs, SDKs, CLIs, and UIs that make ML@Roblox easy to adopt.
Bootstrap and maintain core ML Platform components: Serving Layer, Model Registry, Pipeline Orchestrator, and Training/Inference control planes.
Set technical strategy and oversee development of high scale and reliable infrastructure systems, with clear SLOs for latency, availability, and cost.
Design great developer experiences with paved-road templates, golden paths, opinionated defaults, and clear docs to reduce time-to-first-production.
Instrument the platform to measure adoption, friction, reliability, and cost; use data to prioritize roadmap and validate outcomes.
Partner across organizations (ML Engineering, Data Science, Infra/SRE, Security, Finance) to optimize performance, safety, and spend, especially for GPU-intensive training and high-QPS inference.
Propose and implement new platform tooling to improve time to production for MLEs across the full ML lifecycle.
Stay abreast of industry trends in machine learning and infrastructure to ensure the adoption of leading-edge technologies and practices.
Mentor junior and senior engineers, lead design reviews, and drive cross-team architectural decisions that last.

Have 7+ years of professional experience and have a wealth of system design experience upon which to draw to build a scalable, reliable ML platform for all of Roblox.
Proficient in API design and developer experience—gRPC/REST APIs, SDKs, CLIs, and simple UIs that developers love to use.
A clear communicator who excels at both written and verbal communication across differing levels of technical detail.
Bachelor's degree in Computer Science, Computer Engineering, Data Science, or a similar technical field.

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, and have built ML platform features that are delightful to use

Roles that are based in an office are onsite Tuesday, Wednesday, and Thursday, with optional presence on Monday and Friday (unless otherwise noted).