NVIDIA
Cloud Service Provider
SeniorSoftwareEngineer,NCCLandCUDA-CSPEngagements
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“Senior Software Engineer, NCCL and CUDA - CSP Engagements at NVIDIA. Skills: NCCL, CUDA, parallel programming, performance optimization, system software. root cause functional and performance issues in NCCL and CUDA libraries. Analyze and improve multi-GPU workloads performance through profiling, benchmarking, and tuning”
Industry & Context.
root cause functional and performance issues; solve NCCL and NVSHMEM data movement issues; solve CUDA porting issues; Debug and resolve complex issues
What They're Looking For.
Must Have
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 Have
software architecture experience, Experience with deep learning workloads training and inferencing, Experience conducting performance benchmarking and developing tooling on HPC clusters
What You'll Do.
root cause functional and performance issues in NCCL and CUDA libraries
Analyze and improve multi-GPU workloads performance through profiling
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
Collaborate with customers to understand their workload integration specific challenges to NCCL and CUDIA libraries and suggest tailored solutions aligned with the NVIDIA ecosystem
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
How You'll Work.
Team & Collaboration
Engage with our CSPs; Collaborate with customers; Collaborate with AE, FAE, and solution architects; Collaborate with internal teams; collaborate with partner and customer teams
Communication Scope
Ability to communicate effectively
Full Job Description
NVIDIA is seeking a Senior Software Engineer, NCCL and CUDA specialization to join our Cloud Service Provider (CSP)Engagements team, focusing on ML software stack functionality and performance for datacenter products such as GB300 and Vera Rubin. This role involves working with the customers to understand the functional and performance issues in the libraries layer for deployment at scale. The role combines deep technical expertise in workloads, NCCL and CUDA libraries, frameworks, and system software interaction to solve the customer issues and bring the next generation of innovation. **What you will be doing:** * Engage with our 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. **What we need to see:** * 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
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