What we need to see: M.S. (or equivalent experience) or PHD in Computer Science, or related field with relevant performance engineering and HPC experience 3+ yrs of experience with parallel programming and at least one communication runtime (MPI, NCCL, UCX, NVSHMEM) Experience conducting performance benchmarking and triage on large scale HPC clusters Good understanding of computer system architecture, HW-SW interactions and operating systems principles (aka systems software fundamentals) Implement micro-benchmarks in C/C++, read and modify the code base when required Ability to debug performance issues across the entire HW/SW stack. Proficient in a scripting language, preferably Python Familiar with containers, cloud provisioning and scheduling tools (Kubernetes, SLURM, Ansible, Docker) Adaptability and passion to learn new areas and tools. Flexibility to work and communicate effectively across different teams and timezones Ways to stand out from the crowd: Practical experience with Infiniband/Ethernet networks in areas like RDMA, topologies, congestion control Experience debugging network issues in large scale deployments Familiarity with CUDA programming and/or GPUs Experience with Deep Learning Frameworks such PyTorch, TensorFlow NVIDIA is at the forefront of breakthroughs in Artificial Intelligence, High-Performance Computing, and Visualization. Our teams are composed of driven, innovative professionals dedicated to pushing the boundaries of technology. We offer highly competitive salaries, an extensive benefits package, and a work environment that promotes diversity, inclusion, and flexibility. As an equal opportunity employer, we are committed to fostering a supportive and empowering workplace for all.
