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# Senior Performance Engineer

- **Company:** Nvidia
- **Location:** UK
- **Experience:** Expert
- **Contract:** Permanent contract
- **Skills:** 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, Graphics Processing Unit (GPU), Cloud Platform System, Pytorch, Deep Learning, AI Platforms, Information Technology
- **Published:** October 10, 2026
- **Apply:** https://www.totaljobs.com/job/senior-performance-engineer/nvidia-job108124178

## About the Role

* 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

## Description

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.