System Software Engineer - Performance Lab
NVIDIA Corporation · Santa Clara, CA
$184,000–$356,500from the description
Jun 28, 2026
Santa Clara, CA
Jul 21, 2026
What this job asks for AI summary
A software engineering role within a performance benchmarking team, focused on building and maintaining containerized, GPU-accelerated workloads for financial services applications — spanning deep learning training and inference, portfolio optimization, and backtesting. The work involves running benchmarks at scale on HPC clusters, analyzing results, and developing reference models. Suited to an experienced Python developer with a background in machine learning and an interest in quantitative finance.
Senior level · 8+ years · Santa Clara, CA · Full-time
“or” means any one of them counts — you don't need all of them.
Posted 2 times — it's one opening, so apply once.
We read this from the posting text with AI. Skim the description below before ruling yourself out.
How this req sits in the market our data
Roughly 3,250 people in the Santa Clara, CA area plausibly meet what this posting asks for (software developers). range 2,450–4,250
Applicant volume Heavy — This req sits in a large pool with little in its requirements to thin it, and auto-apply tools fire at everything in the occupation. Applying early and leading with the rare skills below is what gets read.
Most people in this occupation already list these. Still required — just not what gets you shortlisted.
What the occupation pays Median $213,110 (middle half $173,650–$226,080). This posting is about at that midpoint.
Estimated from BLS employment for this occupation and area, per-skill prevalence across our listing corpus, and published wage benchmarks — as of Jul 28, 2026. It is a model, not a headcount.
Why we read it this way (6)
The compensation range spans two internal levels: Level 4 ($184,000–$287,500) and Level 5 ($224,000–$356,500). The pay band fields reflect the full combined range across both levels.
The degree requirement states 'Bachelor's degree … or equivalent experience', so no formal degree is hard-gated.
Version control is required but no specific tool is named; Git is the canonical default and is captured as a proxy for that requirement.
PyTorch, CUDA/GPU computing, Kubernetes/Slurm, and containerization all appear under the 'Ways to stand out from the crowd' section, making them preferred rather than required.
The role sits at the boundary between Software Developer (15-1252) and Data Scientist (15-2051): primary deliverables are containerized GPU workloads and benchmarking software, which tips it toward 15-1252, but the ML training/inference and financial AI model work give 15-2051 a credible claim as runner-up.
No specific work location is stated beyond NVIDIA's general presence; Santa Clara, CA (NVIDIA HQ) is used as the best-fit CBSA. The role does not appear to be remote.
Read the full posting
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