$184,000 – $287,500
Listed on NVIDIA’s own careers site. You apply with them directly — we never stand between you and the employer.
What this role is
NVIDIA is hiring a senior performance engineer to lead benchmarking and optimization of their data center GPU platforms, ensuring they deliver industry-leading performance for AI and HPC workloads. This role suits someone with deep systems knowledge who can identify bottlenecks, tune configurations, and drive improvements across compute, memory, networking, and storage infrastructure.
Our summary, not NVIDIA’s wording. The full posting is on their site.
Skills this role names
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What they ask for
Required
- M.S. or Ph.D. in Computer Science, Electrical Engineering, or related field, or equivalent experience
- 8+ years in performance engineering or system architecture
- Deep knowledge of computer architecture and hardware-software interaction at scale
- Proficiency with Linux perf and NVIDIA Nsight Systems
- GPU computing and parallel programming experience with CUDA
- HPC networking experience with InfiniBand, RoCE, or NVLink
- Programming in Python, C++, and shell scripting
- Strong analytical and problem-solving abilities
- Ability to work with cross-functional global teams
Nice to have
- Experience with AI/ML frameworks like PyTorch, TensorFlow, or JAX
- Knowledge of MPI and collective communications like NCCL
- Distributed training and inference experience
- Familiarity with NVIDIA DGX and HGX platforms
- Experience with containers and cloud provisioning tools like Docker, Kubernetes, or SLURM
- Understanding of storage systems and I/O performance
- Track record of performance optimization in production environments
- Experience with AI code generation tools