Senior Member of Technical Staff, ML Systems

About the Role

Help build and optimize the training and inference systems behind image, video, and world-model workloads. You will improve performance across GPU kernels, distributed execution, and multi-node serving, working with a team focused on making advanced models faster and more efficient.

What You'll Do

• Optimize training and inference performance for image, video, diffusion, and world-model workloads.

• Profile bottlenecks at the kernel, memory, system, and cluster levels using Nsight and related tools.

• 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.

• Build benchmarks and regression tests to preserve performance gains in production.

• Contribute to hardware-aware kernel, runtime, and model co-design.

What We're Looking For

• At least two years of experience in deep learning training or inference systems, distributed systems, or related work, including at least one year of hands-on ML systems or GPU performance work in your current or most recent role.

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

• Direct experience writing kernels for NVIDIA GPUs using CUDA, CUTLASS, Triton, or PTX.

• Authorship of core features in an inference or training framework, rather than deployment or integration work alone.

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

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

• Primary experience in GPU-based ML systems, rather than AMD, FPGA, or custom-accelerator work.

Compensation & Benefits

Base salary is $180,000 to $230,000 USD annually. Visa sponsorship is available.

Location

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