Senior Software Engineer, NCCL and CUDA - CSP Engagements

NVIDIA•Austin, CA

16h

About The Position

NVIDIA is seeking a Senior Software Engineer, NCCL and CUDA specialization to join our Cloud Service Provider (CSP) Engagements team. This role focuses on ML software stack functionality and performance for datacenter products like GB300 and Vera Rubin. You will work with customers to understand and resolve functional and performance issues in the libraries layer for large-scale deployments. The position requires deep technical expertise in workloads, NCCL and CUDA libraries, frameworks, and system software interaction to solve customer issues and drive innovation.

Requirements

Experience with parallel programming models and with communication libraries (MPI, NCCL, NVSHMEM) run time.
Experience with performance optimization and profiling tools (e.g., Nsight, nvprof).
Excellent C/C++ programming and debugging skills, with experience in CUDA development.
Good exposure to PCIe and NVLINK.
Deep understanding of operating systems and data-center system architecture.
Knowledge of high-performance networking like InfiniBand, and RoCE.
Proficient understanding of compute, networking and cloud deployment, specifically on bare-metal and VMs.
BS or MS in Computer Engineering, Computer Science, or related field (or equivalent experience).
Familiarity with containers, cloud provisioning and scheduling tools such as Docker, Kubernetes, SLURM, and Ansible.
8+ years of system software validation experience.
Ability to communicate effectively and collaborate with partner and customer teams.

Nice To Haves

Strong software architecture experience.
Experience with deep learning workloads training and inferencing.
Experience conducting performance benchmarking and developing tooling on HPC clusters.

Responsibilities

Engage with CSPs to root cause functional and performance issues in NCCL and CUDA libraries.
Analyze and improve multi-GPU workloads performance through profiling, benchmarking, and tuning.
Understand and solve NCCL and NVSHMEM data movement issues in multi-node clusters.
Understand and solve CUDA porting issues for customer workloads.
Apply datacenter-specific scheduling and topologies for optimal performance.
Debug and resolve complex issues related to GPU computation, memory, and transports.
Collaborate with customers to understand their workload integration specific challenges to NCCL and CUDIA libraries and suggest tailored solutions aligned with the NVIDIA ecosystem.
Collaborate with AE, FAE, and solution architects to deliver integrated customer solutions and technical documentation.
Collaborate with internal teams to help customers use the latest advancements in CUDA and in NCCL.