Senior Performance Engineer
Remote - Switzerland, Switzerland, ZurichRemoteFirmwarePosted Aug 4, 2026
Overview
- Added in 30 days
- 658
- At this company, still open
Skills named in this posting
- PCIe
- C
- C++
- Python
- CUDA
- PyTorch / TensorFlow
NVIDIA is seeking a highly skilled Senior Performance Engineer to join our Performance and R&D organizations. In this role, you will help build and evolve systems that support performance analysis, telemetry, and optimization for large-scale GPU- and CPU-based clusters used in AI and high-performance computing environments. You will work closely with hardware, networking, firmware, and software teams to collect, analyze, and interpret performance data from live systems. This is a fast-paced R&D environment where system behavior and requirements evolve rapidly, requiring adaptable engineering solutions and strong analytical thinking.
What you’ll be doing:
• Profile, benchmark, and analyze AI and HPC workloads on GPU and CPU clusters
• Explore performance characteristics of high-performance networking and collective communications (e.g., NCCL, RDMA, MPI, RoCE)
• Identify performance bottlenecks across networking, compute, memory, and system architecture
• Develop and enhance performance analysis, benchmarking, and diagnostic tools
• Define performance test plans and establish expectations for new technologies and platforms
• Collaborate across hardware, firmware, networking, systems, and software teams to provide actionable performance insights
• Support telemetry collection and data refinement efforts to enable accurate performance analysis
• Maintain high standards for data quality, reproducibility, and traceability of performance results
What we need to see:
• B.Sc. or M.Sc. in Computer Science, Computer Engineering, Software Engineering, or equivalent experience
• 5+ years of experience in performance analysis, systems engineering, or HPC/AI infrastructure
• Demonstrated expertise in performance analysis skills and methodologies
• Hands-on experience with high-performance networking (RDMA, MPI, NCCL, congestion control)
• Strong understanding of system performance metrics (latency, throughput, resource utilization)
• Exposure to hardware, firmware, or embedded telemetry environments
• Strong analytical, problem-solving, and communication skills
• Ability to work effectively in cross-functional, fast-paced R&D teams
Ways to stand out from the crowd:
• Knowledge of CUDA, NCCL internals, and congestion control algorithms
• Deep system-level understanding of CPU architectures, GPUs, HCAs, memory, and PCIe
• Experience with NVIDIA GPUs, CUDA, and deep learning frameworks such as PyTorch or TensorFlow
• Experience with cloud platforms
• Proficiency in Python; experience with Bash and C/C++ is a plus as well as a strong experience working in Linux environments
At NVIDIA, we are passionate about supercomputing and powerful ground-breaking technologies. Our products span many areas, such as: high-performance computing (HPC), Machine Learning, cloud services, storage and more - and we've only scratched the surface of what can be accomplished. We need hardworking and creative people to help us seek some of these outstanding opportunities. With highly competitive salaries and a comprehensive benefits package, NVIDIA is widely considered to be one of the technology world’s most desirable employers. We have some of the smartest engineers in the world working for us and, due to extraordinary growth, our elite engineering teams are fast-growing fast. If you're a creative and autonomous manager with a sincere passion for technology, we want to hear from you.
NVIDIA is committed to fostering a diverse work environment and proud to be an equal opportunity employer. As we highly value diversity in our employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.
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Original posting: jobs.nvidia.com
RISC-V ecosystem
NVIDIA Corporation in the RISC-V ecosystem
RISC-V International: Premier Board
Founded in 1993, NVIDIA is an AI computing company. The company is headquartered in Santa Clara, California.
- NVIDIA is bringing CUDA platform support to RISC-V, i.e. allowing a RISC-V CPU to host CUDA GPU applications
- Publicly credited the RVA23 profile as the enabler: "We wouldn't have considered porting CUDA to RISC-V without it"
- Active in RISC-V International profile/standards work and a frequent presence in RISC-V ecosystem coverage
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