Member of Technical Staff, ML Systems
True Talent Solutions Partners · Menlo Park · onsite
ABOUT THE ROLE
Join an AI and machine learning team building high-performance training and inference systems for image, video, and world-model workloads. You will improve performance across the stack, from GPU kernels to distributed training and serving.
WHAT YOU'LL DO
- Optimize training and inference performance for image, video, and world-model workloads.
- Profile bottlenecks at the kernel, memory, system, and cluster levels using Nsight and related tools.
- Implement low-level optimizations with 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, RoCE, and disaggregated serving approaches.
- Build benchmarks and regression tests to preserve performance gains in production.
- Co-design kernels, runtimes, and models with hardware in mind.
WHAT WE'RE LOOKING FOR
- At least 2 years of experience in deep learning training or inference systems, GPU performance, or distributed systems.
- Hands-on ML systems or GPU performance experience in a recent role, including work on inference or training performance.
- Experience authoring core features in an inference or training framework, such as vLLM, SGLang, TensorRT-LLM, or Megatron.
- Direct experience writing 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.
COMPENSATION & BENEFITS
Base salary is $180,000 to $260,000 annually. Visa sponsorship is available.
LOCATION
On-site in Menlo Park, California, United States.