Training Infrastructure Engineer

In this role, you’ll focus on the full training stack - profiling GPU behavior, debugging training pipelines, improving throughput, choosing the right parallelism strategies, and designing the infrastructure that lets us train models efficiently at scale. You’ll work across cluster management, model training, efficient data pipelines for video and audio, inference and optimizing pytorch code. Your work will shape the foundation on which all of our generative models are built and iterated.

• Find ideal training strategies (parallelism approaches, precision trade-offs) for a variety of model sizes and compute loads
• Profile, debug, and optimize single and multi-GPU operations using tools like Nsight and stack trace viewers to understand what's actually happening at the hardware level