Level

NVIDIA

Senior Performance Engineer

NVIDIA is hiring a Senior Performance Engineer for a remote role open to applicants in United Kingdom. Level rates it ; you can apply on Level.

AI in this role

pytorchjax

NVIDIA has been transforming computer graphics, PC gaming, and accelerated computing for more than 25 years. It’s a unique legacy of innovation that’s fueled by great technology—and amazing people.

Join NVIDIA's DGX Cloud AI Efficiency Team means advancing the performance, efficiency, and resiliency of large-scale AI workloads. We help AI researchers and platform teams understand end-to-end behavior across GPUs, networking, storage, and software stacks.

We are seeking a Performance Engineer to characterize workloads, establish performance baselines, diagnose bottlenecks, and drive optimizations from investigation through deployment. Your work will shape scalable DGX Cloud systems, turn complex measurements into prioritized engineering decisions, and continuously raise the performance and reliability of AI workloads. Join our technically diverse team of infrastructure experts to unlock more efficient AI at scale.

What you'll be doing:

  • Analyze end-to-end performance of large-scale AI workloads across compute, network, storage, and software stacks.

  • Design and execute rigorous performance studies to establish baselines, diagnose regressions, and quantify bottlenecks.

  • Define performance and efficiency evaluation methodologies, benchmarks, and success metrics for AI workloads.

  • Use profiling, observability, and data analysis to turn performance measurements into actionable optimization plans.

  • Partner with deep learning engineers, platform teams, and GPU architects to validate and deliver performance improvements.

  • Communicate performance findings, tradeoffs, and recommendations clearly to influence system and software design decisions.

What we need to see:

  • BS or higher degree in computer science, computer engineering, or a related field, with 12+ years of experience

  • Strong programming skills in C++ and Python, with the ability to build reliable analysis and automation workflows

  • Solid foundation in operating systems, computer architecture, and distributed systems

  • Experience with performance engineering, benchmarking, profiling, and optimization of complex software or systems

  • Ability to communicate technical findings, prioritize high-impact work, and build alignment across teams

Ways to stand out from the crowd:

  • Experience analyzing large-scale AI clusters or distributed training and inference workloads

  • Experience with CUDA, GPU computing systems, and GPU performance analysis

  • Hands-on experience with deep learning frameworks such as PyTorch or JAX/XLA

  • Deep understanding of system-level performance analysis, workload characterization, and optimization

NVIDIA leads the way in groundbreaking developments in Artificial Intelligence, High-Performance Computing, and Visualization. The GPU, our invention, serves as the visual cortex of modern computers and is at the heart of our products and services. Our work opens up new universes to explore, enables amazing creativity and discovery, and powers what were once science fiction inventions, from artificial intelligence to autonomous cars. NVIDIA is looking for exceptional people like you to help us accelerate the next wave of artificial intelligence.

How we rate this

Senior Performance Engineer at NVIDIA rates 89 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. Open the description and count.

Prepare for this job

A free preview built only from this posting: what it asks for, what you could be asked in an interview, and how to adjust your resume.

Skills and AI tools this role asks for

PyTorchJax

Questions you could be asked

  1. What's a project where you used PyTorch hands-on?
  2. Walk me through how you've used Jax in your day-to-day work.
  3. How would you decide a model or AI system is ready to ship?
  4. 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 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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