1 day ago
Remote, United Kingdom +2 moreSenior
Responsibilities
- Analyze end-to-end performance of large-scale AI workloads across compute, network, storage, and software stacks.
- Design and execute 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 develop 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 to influence system and software design decisions.
Requirements
- BS or higher degree in computer science, computer engineering, or a related field.
- 12+ years of experience.
- Strong programming skills in C++ and Python, including the ability to build reliable analysis and automation workflows.
- Strong 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.
- Preferred: experience analyzing large-scale AI clusters or distributed training and inference workloads.
- Preferred: experience with CUDA, GPU computing systems, and GPU performance analysis.
- Preferred: hands-on experience with PyTorch or JAX/XLA.
- Preferred: deep understanding of system-level performance analysis, workload characterization, and optimization.
About Nvidia
Nvidia designs and sells GPUs and accelerated computing platforms for data centers, AI/ML, graphics, gaming, and automotive, monetizing through hardware, software platforms (CUDA, AI frameworks), and systems like DGX and networking. Customers include cloud providers, enterprises, researchers, and OEMs. Founded in 1993 and headquartered in Santa Clara, it is a public company traded on NASDAQ under NVDA.