Client Roles
ABOUT THE ROLE
Join an AI team building high-performance training and inference systems for image, video, and world-model workloads. You will improve efficiency across GPU kernels, distributed engines, and multi-node systems, helping make advanced models faster to train and serve.
WHAT YOU'LL DO
- Optimize system and GPU performance for training and inference across image, video, and world-model workloads.
- Use Nsight and related tools to identify and remove kernel, memory, system, and cluster bottlenecks.
- Implement low-level optimizations using CUDA and Triton.
- Design and improve distributed inference and training engines for diffusion models.
- Improve communication performance across GPUs and nodes using NCCL, RDMA, InfiniBand, RoCE, and disaggregated serving techniques.
- Build benchmarking and regression harnesses to maintain performance gains in production.
- Co-design kernels, runtimes, and models with hardware characteristics 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, including 1 or more years of hands-on ML systems or GPU performance work in a recent full-time role.
- Experience authoring core features in an inference or training framework, such as vLLM, SGLang, TensorRT-LLM, Megatron, or a comparable system.
- Hands-on experience writing kernels for NVIDIA GPUs using CUDA, CUTLASS, Triton, or PTX.
- Strong machine learning and computer science fundamentals, supported by a degree in computer science or a related quantitative