NVIDIASenior Firmware Performance Engineer
NVIDIA is hiring a Senior Firmware Performance Engineer. Level rates it ; you can apply on Level.
AI in this role
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
How we rate this
Senior Firmware Performance Engineer at NVIDIA rates 87 out of 100 for how much of the daily work is AI. That makes it Builds AI (AI Level 4 of 4). The level is about AI in the job, not seniority.
Builds AI. The job is building AI systems.
- ●●●● Builds AI80 to 100
- ●●●○ Works on AI60 to 79
- ●●○○ Uses AI40 to 59
- ●○○○ Little AI0 to 39
Levels come from how often the tools, models and workflows of the role are named in the posting itself. Open the description and count.
Prepare for this job
Built from this posting and from similar jobs on Level.
Skills and AI tools this role asks for
Questions you could be asked
- What's a project where you used PyTorch hands-on?
- Walk me through how you've used TensorFlow in your day-to-day work.
- How would you decide a model or AI system is ready to ship?
- Tell me about a time a model underperformed in production. How did you find out, and what did you change?
Adapt your resume
- List these exact terms on your resume: PyTorch and TensorFlow. An applicant tracking system matches the wording, not the idea.
- Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
- Lead with what you built, trained or shipped. This role is judged on the AI system itself, not the tools around it.
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