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NVIDIA

Senior Performance Engineer - Deep Learning

NVIDIA is hiring a Senior Performance Engineer - Deep Learning in Santa Clara, United States. It pays $152k-$242k a year and Level rates it ; you can apply on NVIDIA.

Level's read on this job

  • On Level's scale, this role is Builds AI ●●●●: the job is building AI systems.
  • The posting mentions OpenAI, PyTorch and JAX among its tools and skills.
  • Level classes it as a senior role.
  • NVIDIA has 2,800+ other open roles on Level.

AI in this role

OpenAIPyTorchJAX

Our Deep Learning models performance engineering team at NVIDIA is hiring software engineers at all experience levels to build and optimize the libraries and tools that enable Deep Learning Researchers and Engineers to design, develop, and deploy efficient AI applications. We are an ambitious and diverse team that builds optimizations directly into mainstream open source Deep Learning frameworks - PyTorch and JAX, which boost the performance at all levels of NVIDIA's AI stack. Our team has a wide collaborative footprint, working not only with multiple teams across NVIDIA but also with the broader open-source community to deliver SOTA Deep Learning performance on the best AI platform in the world!

What you will be doing:

  • Build and support Transformer Engine, the open-source library for accelerating the training of Large Language Models.

  • Collaborate on systems research that improves Deep Learning model performance, such as training using extremely low precision, parallelism methods, etc.

  • Implement, benchmark, and optimize new Deep Learning models such as LLMs straight out of groundbreaking research to scale efficiently on NVIDIA GPUs and systems.

  • Build and contribute to NVIDIA submissions on community benchmarks such as MLPerf.

  • Engage with the open-source community as well as support enterprise customers and partners by delivering the benefits of NVIDIA’s latest hardware and software innovations.

  • Influence the design of new hardware generations and core platform software components for NVIDIA hardware and systems.

What we need to see:

  • BS or equivalent experience in Computer Science, Electrical Engineering, or a related field.

  • 3+ years of experience in C++ and Python programming.

  • Strong background, experience, or coursework in parallel systems programming, preferably on GPUs.

  • Knowledge of Computer Architecture, Code Optimization, and/or Operating Systems.

  • Proven experience in developing large software projects.

  • Excellent verbal and written communication skills.

Ways to stand out from the crowd:

  • Experience in PyTorch, JAX, or any other DL framework.

  • Experience with performance analysis, profiling, and code optimization techniques, especially with multi-GPU or multi-node systems.

  • Knowledge of modern LLM architectures, attention mechanisms, and/or low-level DL libraries such as cuBLAS, cuDNN, and cuSOLVER.

  • Experience in writing GPU kernels using any of - CUDA, OpenAI Triton, CuTeDSL, Pallas, or other similar libraries.

  • Any past contributions to the open source community and/or experience working with multidisciplinary teams also showcase readiness for the team's responsibilities.

Your base salary will be determined based on your location, experience, and other objective job-related factors. The expected base salary ranges for this position are:
152,000 USD – 241,500 USD for Level 3; and 184,000 USD – 287,500 USD for Level 4.

You will also be eligible for equity and benefits.

Applications for this job will be accepted at least until November 9, 2026.

This posting is for an existing vacancy.

NVIDIA uses AI tools in its recruiting processes.

NVIDIA is committed to fostering an inclusive work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future 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.

How we rate this

Senior Performance Engineer - Deep Learning at NVIDIA rates 95 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.

Classification

Builds AI. The job is building AI systems.

  1. ●●●● Builds AI80 to 100
  2. ●●●○ Works on AI60 to 79
  3. ●●○○ Uses AI40 to 59
  4. ●○○○ Little AI0 to 39

Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.

Prepare for this job

Built from this posting and from similar jobs on Level.

Skills and AI tools this role asks for

OpenAIPyTorchJAX

Questions you could be asked

  1. What's a project where you used OpenAI hands-on?
  2. Walk me through how you've used PyTorch in your day-to-day work.
  3. What are the limits of JAX that you've run into, and how did you work around them?
  4. How would you decide a model or AI system is ready to ship?
  5. 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: OpenAI, PyTorch, and JAX. 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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