Senior Performance Engineer

Nvidia
UK
11 days ago
Apply on nvidia.wd5.myworkdayjobs.com
Prepare application

Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Experience level
Expert
Working hours
Regular working hours

Tech stack

Artificial Intelligence Data Analysis C++ (Programming Language) Profiling Nvidia CUDA Computer Programming Computer Engineering Distributed Computing Environment Distributed Systems General-Purpose Computing on Graphics Processing Units Python (Programming Language) Software Engineering
+3 more
Pytorch Deep Learning Information Technology

Job description

  • 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.

Requirements

  • 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

About the company

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., 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.

Apply for this position

This job is hosted externally. Click below to view the full posting and apply.

Apply on nvidia.wd5.myworkdayjobs.com
Prepare application

Good distractions

Talks and stories from around this role — technically off-topic, practically not.

2:33 min

Architecting CUDA and the AI software stack

Michael Kagan Michael Kagan +1 · World Congress 2026 Europe

6:21 min

Previewing upcoming hardware acceleration capabilities for Python environments

Chris Heilmann +2 · LIVE

47 sec

Profiling native execution calls with async-profiler

Gonzalo Ortiz Jaureguizar Gonzalo Ortiz Jaureguizar · World Congress 2026 Europe

2:35 min

Preventing remote code execution in PyTorch models

Balázs Kiss · World Congress 2023

1:37 min

Accelerating compute with focused developer tools

Julia Koch Julia Koch +1 · World Congress 2026 Europe

3:30 min

Transitioning from CUDA software architect to user

Stephen Jones · Coffee With Developers

Videos

See all

Related articles

See all