Senior Software Engineer, NCCL, CUDA

🕒 May 6

🏄 California, Texas, +1 more states – Remote

🏄 California – Remote 🤠 Texas – Remote ☕ Washington – Remote

💵 $184k - $287.5k / year

⏰ Full Time

🟠 Senior

🧑‍💻 Full-stack Engineer

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NVIDIA

WebsiteLinkedInAll Job Openings

10,000+ employees

Founded 1993

🤖 Artificial Intelligence

🎮 Gaming

Artificial Intelligence • Gaming • Automotive

NVIDIA is a leading technology company specializing in accelerated computing and artificial intelligence. NVIDIA pioneers advancements in graphical processing units (GPUs), cloud computing, data centers, and virtual reality, with a focus on gaming, automotive, healthcare, and robotics industries. The company's innovations, such as NVIDIA Omniverse, transform traditional digital processes by enabling high-fidelity simulations and rendering tasks. Their applications span various industries, from autonomous vehicles using NVIDIA DRIVE to healthcare solutions with NVIDIA Clara, and AI-driven analytics and workflows.

📋 Description

• 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 CUDA 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.

🎯 Requirements

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

🏖️ Benefits

• equity • benefits