Used Tools & Technologies
Machine LearningRequired Skills & Competences
Tag name is followed by "@" symbol and proficiency level value.
About proficiency levels:
- 1-2 — basic awareness. Minimal hands-on experience, and a rudimentary understanding of the technology's purpose;
- 3-6 — daily use. Comfortable and regular usage, capable of handling common tasks and challenges related to the technology;
- 7-9 — you are an expert, you can teach others, you know all the pitfalls and tricks;
- 10 — exceptional knowledge, comprehensive understanding, and adeptness in all aspects of the technology, including advanced problem-solving. Think twice before claiming or demanding such level.
Ansible @ 3
Docker @ 3
Kubernetes @ 3
Communication @ 4
Networking @ 4
Parallel Programming @ 4
Performance Optimization @ 4
Debugging @ 4
System Architecture @ 7
CUDA @ 4
GPU @ 4
Deep Learning @ 4
AI @ 4
InfiniBand @ 4
Profiling @ 4
NCCL @ 4
Slurm @ 3
HPC @ 4
NVLink @ 4
- 1-2 — basic awareness. Minimal hands-on experience, and a rudimentary understanding of the technology's purpose;
- 3-6 — daily use. Comfortable and regular usage, capable of handling common tasks and challenges related to the technology;
- 7-9 — you are an expert, you can teach others, you know all the pitfalls and tricks;
- 10 — exceptional knowledge, comprehensive understanding, and adeptness in all aspects of the technology, including advanced problem-solving. Think twice before claiming or demanding such level.
Details
NVIDIA is seeking a Senior Software Engineer with NCCL and CUDA specialization to join the Cloud Service Provider (CSP) Engagements team. The role focuses on ML software stack functionality and performance for datacenter products (for example GB300 and Vera Rubin), working with customers to understand and resolve functional and performance issues in the libraries layer for deployment at scale. The position combines deep technical expertise in workloads, NCCL and CUDA libraries, frameworks, and system software interaction to solve customer issues and drive next-generation innovation.
Responsibilities
- Engage with CSP customers to root cause functional and performance issues in NCCL and CUDA libraries.
- Analyze and improve multi-GPU workload 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 workload integration challenges with 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 NCCL.
Requirements
- Experience with parallel programming models and communication libraries (MPI, NCCL, NVSHMEM).
- Experience with performance optimization and profiling tools (e.g., Nsight, nvprof).
- Excellent C/C++ programming and debugging skills; experience in CUDA development.
- Good exposure to PCIe and NVLINK.
- Deep understanding of operating systems and datacenter system architecture.
- Knowledge of high-performance networking (InfiniBand, 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.
Ways to Stand Out
- Strong software architecture experience.
- Experience with deep learning workloads (training and inference).
- Experience conducting performance benchmarking and developing tooling on HPC clusters.
Compensation
Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary ranges provided in the posting:
- Level 4: 184,000 USD - 287,500 USD
- Level 5: 224,000 USD - 356,500 USD
You will also be eligible for equity and benefits.
Other Information
- Location provided: Santa Clara, CA, United States.
- Applications for this job will be accepted at least until May 9, 2026.
- NVIDIA uses AI tools in its recruiting processes.
- NVIDIA is an equal opportunity employer and commits to fostering a diverse work environment.