Staff ML Infrastructure Engineer, ML Platform & Technology - Pre-training Infrastructure

What you'll do

• Optimize performance for large-scale foundation model training on TPUs to improve efficiency and scalability.
• Profile and optimize JAX/XLA workloads across compute, memory, communication, and compilation layers.
• Develop and optimize high-performance TPU kernels for critical operations like attention and Mixture-of-Experts.
• Optimize distributed training techniques, sharding strategies, and collective communication over TPU interconnects.
• Research and implement new performance improvements across the JAX, XLA, and TPU stack.
• Build performance profiling, benchmarking, and automated tuning tools for large-scale training workloads.
• Lead complex technical projects and mentor engineers in specialized areas of expertise.

What we're looking for

• Bachelor's degree in Computer Science, Engineering, or a related field.
• Advanced degree in Computer Science, Engineering, or a related field is preferred.
• 6+ years of experience building or optimizing high-performance ML or distributed systems.
• Proficiency in Python or other relevant programming languages.
• Strong understanding of distributed systems, parallel computing, and performance optimization.
• Experience profiling and optimizing compute-, memory-, or communication-intensive workloads.
• Experience with accelerators such as TPU or GPU and knowledge of accelerator architecture.
• Experience with JAX, XLA, PyTorch, or other ML compiler/runtime stacks.