Senior Performance Engineer - Deep Learning
Company websitenvidia.com (NVIDIA, opens in new tab)
Base salary $152,000 to $287,500
Employer-published annual base salary, USD. Advertised base range in Santa Clara, CA
You apply on the employer's own site. Six Figure Work does not handle applications.
- LocationSanta Clara, CA
- WorkplaceWorkplace not stated
- Status at last checkSource accepting applications when checked
- Last checked (51 min ago) · observed since
About this job
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.
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.Source: NVIDIA on Workday · View original posting (opens in new tab)
Pay in context
This role's base floor ($152,000) is above 21% of the 1,468 Data & ML roles in California listed on this site; 20 others list the same floor. Their median floor is $190,000; the middle half runs from $160,000 to $229,900.
Only jobs on this site count, and each one publishes a base salary of $100,000 or more, so this compares six-figure jobs with each other, not with the whole market. Computed Nov 6, 2026.
This listingSenior Performance Engineer - Deep Learning$152,000 to $287,500
Senior Networking Architect$152,000 to $287,500
Solutions Architect, AI and ML$152,000 to $287,500
Infrastructure Solutions Architect - OEM$152,000 to $287,500
Senior Software Engineer, CUTLASS Performance$152,000 to $287,500
Senior Software Engineer - Distributed Systems Engineer, EDA Infrastructure$152,000 to $287,500
Senior Graphics Driver Engineer$152,000 to $241,500
Chart as a table
| Role | Published base |
|---|---|
| Senior Performance Engineer - Deep Learning (this listing) | $152,000 - $287,500 |
| Senior Networking Architect | $152,000 - $287,500 |
| Solutions Architect, AI and ML | $152,000 - $287,500 |
| Infrastructure Solutions Architect - OEM | $152,000 - $287,500 |
| Senior Software Engineer, CUTLASS Performance | $152,000 - $287,500 |
| Senior Software Engineer - Distributed Systems Engineer, EDA Infrastructure | $152,000 - $287,500 |
| Senior Graphics Driver Engineer | $152,000 - $241,500 |
Observed changes
- First observed on the employer's board
- Began meeting the published-salary criteria
- Observed since
- Employer-stated posting date
- 2026-11-05
Where this pay comes from
Location as the employer wrote it: US, CA, Santa Clara (Levels 3-4 combined)
152,000 USD – 241,500 USD for Level 3; and 184,000 USD – 287,500 USD for Level 4.
- Method
- Employer text, read with fixed rules and re-verified
- Checked
- Rule set
- us-base-v2
The pay passage appears in the employer's own job text. Fixed, deterministic rules located it, and the passage below was checked against the stored copy of the posting.
What we verified
- The pay figures come from the employer's own listing, quoted exactly above.
- The pay is an annual base salary in US dollars with a minimum of at least $100,000.
- The role was publicly listed on the employer's job board when last checked.
We do not verify what the employer will actually offer, whether the employer is still recruiting for the role, or anything beyond what the employer published. Full methodology.
