Senior Performance Engineer

🔥 0 minutes ago

🌐 United Kingdom, Switzerland, +1 more countries – Remote

🇬🇧 United Kingdom – Remote 🇨🇭 Switzerland – Remote 🇩🇪 Germany – Remote

⏰ Full Time

🟠 Senior

👷🏻‍♀️ Engineer

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NVIDIA

WebsiteLinkedInAll Job Openings

10,000+ employees

Founded 1993

🏥 Healthcare

🏭 Manufacturing

🤖 Artificial Intelligence

Healthcare • Manufacturing • Artificial Intelligence

NVIDIA is a leading technology company specializing in accelerated computing and artificial intelligence. NVIDIA pioneers advancements in graphical processing units (GPUs), cloud computing, data centers, and virtual reality, with a focus on gaming, automotive, healthcare, and robotics industries. The company's innovations, such as NVIDIA Omniverse, transform traditional digital processes by enabling high-fidelity simulations and rendering tasks. Their applications span various industries, from autonomous vehicles using NVIDIA DRIVE to healthcare solutions with NVIDIA Clara, and AI-driven analytics and workflows.

📋 Description

• 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 • Ability to build reliable analysis and automation workflows • 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 • 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