Principal Machine Learning Platform Engineer, Foundation AI

Overview

Principal Platform Engineer to treat the ML platform as a product, turning complex ML/AI infrastructure into durable APIs, SDKs, CLIs and UIs for internal developers, and setting direction end to end.

What you'll do

• 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.

What you'll need

• 10+ years of professional experience with a wealth of system design experience to build a scalable, reliable ML platform.
• Proficient in API design and developer experience: gRPC/REST APIs, SDKs, CLIs, and simple UIs that developers love to use.
• A track record of building internal platforms that developers love.
• A code machine: designs and communicates ideas but also actually ships product.
• Obsesses about user feedback and drives towards getting platform features in customers' hands.
• 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.

Nice to have

• 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.
• Built ML platform features that are delightful to use.
• Passionate about infrastructure-as-code and automating painful manual processes.
• Pushes for platform solutions that don't leave on-call teams carrying the burden of design choices.
• Passionate about supporting ML engineers to meet and understand their needs, and translating them into clean, durable platform abstractions.

Details

• Based at headquarters in San Mateo, CA.
• Onsite Tuesday, Wednesday, and Thursday, with optional presence on Monday and Friday.
• Full-time employment with equity compensation eligibility.