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Salary: USD 243,290 - 312,970 / annual
Roblox is seeking a Senior Machine Learning Platform Engineer to own the ML Platform that 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.
You will own the platform as a product end-to-end: define requirements, write RFDs, and ship APIs, SDKs, CLIs, and UIs that make ML@Roblox easy to adopt. You'll bootstrap and maintain core ML Platform components including the Serving Layer, Model Registry, Pipeline Orchestrator, and Training/Inference control planes. You'll set technical strategy and oversee development of high-scale, reliable infrastructure systems with clear SLOs for latency, availability, and cost.
Key responsibilities include designing great developer experiences with paved-road templates, golden paths, and opinionated defaults to reduce time-to-first-production. You'll instrument the platform to measure adoption, friction, reliability, and cost, using data to prioritize roadmap and validate outcomes. You'll 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.
Additionally, you'll propose and implement new platform tooling to improve time to production for ML engineers across the full ML lifecycle, stay abreast of industry trends in machine learning and infrastructure, mentor junior and senior engineers, lead design reviews, and drive cross-team architectural decisions.
Roblox connects tens of millions of people daily to explore, create, play, learn, and connect in 3D immersive digital experiences. The company is on a mission to connect a billion people with optimism and civility.
Requirements:
- 7+ years of professional experience with strong system design expertise
- Proficiency in API design and developer experience (gRPC/REST APIs, SDKs, CLIs, UIs)
- Strong coding skills with ability to design, communicate ideas, and ship product
- Passion for infrastructure-as-code and automating manual processes
- Experience supporting ML engineers and translating needs into clean platform abstractions
- Excellent written and verbal communication across varying technical levels
- Bachelor's degree in Computer Science, Computer Engineering, Data Science, or similar technical field
- Good to have: end-to-end ML model lifecycle experience (model serving, training, model CI/CD, GPU resource management)
