Senior Member of Technical Staff, ML Systems

About the Role

Join an AI/ML infrastructure team building high-performance training and inference systems for image, video, and world-model workloads. You will improve efficiency across GPU kernels, distributed execution, and multi-node serving, helping make demanding models faster and more practical to run.

What You'll Do

• Optimize training and inference performance across GPU, system, and cluster layers.

• Use Nsight and related profiling tools to identify bottlenecks in kernels, memory, systems, and clusters.

• Implement low-level GPU optimizations using CUDA and Triton.

• Design and improve distributed training and inference engines for diffusion models.

• Improve communication performance across GPUs and nodes using NCCL, RDMA, InfiniBand, or RoCE, and support disaggregated serving.

• Build benchmarks and regression tests to ensure performance improvements hold in production.

• Co-design kernels, runtimes, and models with hardware capabilities in mind.

What We're Looking For

• At least 2 years of experience in deep learning training or inference systems, or distributed systems, including at least 1 year of recent, hands-on ML systems or GPU performance work.

• Experience authoring core features in an inference or training framework, rather than focusing only on deployment or integration.

• Hands-on NVIDIA GPU kernel development with CUDA, CUTLASS, Triton, or PTX; this role requires writing kernels directly.

• Experience improving inference or training performance through GPU kernels, runtimes, or distributed execution.

• Strong machine learning and computer science fundamentals, and a degree in computer science or a related quantitative field. New graduates should have a particularly strong academic background.

• Experience with PyTorch and profiling tools such as Nsight; familiarity with NCCL and RDMA is relevant.

• Background optimizing diffusion, video, image, or other multimodal workloads is valuable.

Compensation & Benefits

Annual salary range: $180,000 to $230,000 USD. Visa sponsorship is available.

Location

On-site in Menlo Park, California, United States.