Member of Technical Staff, ML Systems
True Talent Solutions Partners · Menlo Park · onsite
ABOUT THE ROLE
Join an AI/ML team building efficient training and inference systems for image, video, and world-model workloads. You will improve performance across the stack, from GPU kernels to distributed, multi-node systems.
WHAT YOU'LL DO
- Optimize training and inference performance for image, video, and world-model workloads.
- Profile and address bottlenecks across GPU kernels, memory, systems, and clusters using tools such as Nsight.
- Implement low-level optimizations in CUDA and Triton.
- Design and improve distributed training and inference engines for diffusion models.
- Improve communication performance across GPUs and nodes using technologies such as NCCL, RDMA, InfiniBand, and RoCE.
- Build benchmarking and regression tools to help sustain performance improvements 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, distributed systems, or related ML systems work.
- Hands-on experience with GPU performance or ML systems in a recent role, including work on inference or training performance.
- Experience authoring core features in an inference or training framework, rather than focusing only on deployment or integration.
- Directly written kernels for NVIDIA GPUs using CUDA, CUTLASS, Triton, or PTX.
- Strong machine learning and computer science fundamentals, with a degree in computer science or a related quantitative field.
- Experience optimizing diffusion, video, image, or other multimodal workloads is valuable.
- Experience with PyTorch, Nsight, NCCL, and RDMA is relevant to the role.
COMPENSATION & BENEFITS
Base salary is $180,000 to $260,000 annually. Visa sponsorship is available.
LOCATION
On-site in Menlo Park, California, United States.