As a Senior / Principal Recommendations Infrastructure Engineer on ML Platform you will build the next generation of ML Ecosystem Tooling for recommendation systems. ML Platform today supports billions of requests per day across our homepage, marketplace, economy, and more. We are looking for accomplished engineers to help build out the next generation of ML platform tooling for recommender systems in a quickly innovating space.

You Are:

• Have 4+ years of professional experience and a tool chest of system design experience upon which to draw to build scalable, reliable platforms for all of Roblox.
• Have significant experience running large-scale recommendation systems that recommend hundreds of millions of items to millions of users.
• Experienced building complex distributed systems that scale to real-time ML inference serving millions of QPS, particularly for real-time recommendation systems.
• Passionate about supporting and working cross functionally with internal partners (Data Scientists and ML Engineers) to meet and understand their needs.
• A reliability nut: you love digging into tricky postmortems and identifying and fixing weaknesses in complicated systems.
• Ideally familiar with ML model inference frameworks like Triton Inference Server, TensorRT, KServe.
• Bachelor's degree or higher in Computer Science, Computer Engineering, Data Science, or a similar technical field.

You Will:

• Set technical strategy and oversee development of high scale, reliable infrastructure systems for recommender systems, especially as we scale up both inference qps and model size.
• Dig into performance bottlenecks all along the recommendation inference stack, spanning from model optimizations to infrastructure optimizations.
• Stay abreast of industry trends in machine learning and infrastructure to ensure the adoption of leading-edge technologies and practices.
• Bootstrap and maintain infrastructure for ML Platform components--Serving Layer, Metadata Store, Model Registry, and Pipeline Orchestrator.
• Partner across organizations to build tooling, interfaces, and visualizations that make the ML@Roblox a delight to use.