Principal Model Optimization Engineer

Every day tens of millions of people come to Roblox to explore create play learn and connect with friends in 3D immersive digital experiences all created by our global community of developers and creators.

At Roblox were building the tools and platform that empower our community to bring any experience that they can imagine to life. Our vision is to reimagine the way people come together from anywhere in the world and on any device. Were on a mission to connect a billion people with optimism and civility and looking for amazing talent to help us get there.

A career at Roblox means youll be working to shape the future of human interaction solving unique technical challenges at scale and helping to create safer more civil shared experiences for everyone.

ML Platform @ Roblox today supports hundreds of ML use cases and billions of inferences per day across Discovery Safety Engine and much more. As a Model Optimization engineer on ML Platform you will be responsible for digging deep into model internals to optimize performance for both training and inference. We are looking for accomplished engineers to help us maximize performance of our platform.

You Will:

• Optimize machine learning models for performance on GPU architectures focusing on both training and inference workflows.
• Conduct low-level performance profiling analysis to identify bottlenecks in existing machine learning pipelines and propose actionable improvements.
• Contribute to the development of best practices and tooling for model optimization and deployment.
• Collaborate with cross-functional teams including data scientists and software engineers to integrate and deploy optimized models into production environments.
• Partner across organizations to build tooling interfaces and visualizations that make the a delight to use.

You Have:

• 6 years of professional experience and a tool chest of system design experience upon which to draw to build performant systems for all of Roblox.
• Have significant experience debugging GPUs - reading GPU profiles debugging Xid errors etc.
• Proficient in advanced tools and frameworks (e.g. CUDA Triton TensorRT) to enhance model execution speed and reduce latency.
• Experience with model optimization techniques for LLMs such as speculative decoding continuous batching quantization etc.
• A performance nut; you love pushing the limits of whats possible whether its squeezing every last ounce of efficiency from a GPU fine-tuning algorithms for peak speed or innovating new techniques to enhance model performance
• A generalization advocate: youre passionate about building tools and frameworks that consistently deliver improvements in model performance.
• Passionate about supporting internal partners (data scientists and ML Engineers) to meet and understand their needs.
• A Bachelors degree in Computer Science Computer Engineering Data Science or a similar technical field.