HPC System Engineer

<div class="content-intro"><p><strong data-stringify-type="bold">Why work at Nebius<br></strong>Nebius is leading a new era in cloud computing to serve the global AI economy. We create the tools and resources our customers need to solve real-world challenges and transform industries, without massive infrastructure costs or the need to build large in-house AI/ML teams. Our employees work at the cutting edge of AI cloud infrastructure alongside some of the most experienced and innovative leaders and engineers in the field.</p> <p><strong>Where we work<br></strong>Headquartered in Amsterdam and listed on Nasdaq, Nebius has a global footprint with R&amp;D hubs across Europe, North America, and Israel. The team of over 1400 employees includes more than 400 highly skilled engineers with deep expertise across hardware and software engineering, as well as an in-house AI R&amp;D team.</p></div><h3><strong><span data-contrast="auto">The role</span></strong><span data-ccp-props="{}">&nbsp;</span></h3> <p>We are seeking a highly skilled <strong data-renderer-mark="true">Systems Engineer (Cloudmeter)</strong> to join our team to support <strong data-renderer-mark="true">benchmarking of GPU platforms</strong> for machine learning and AI workloads. You will play a critical role in evaluating the performance of GPU-based hardware for various deep learning and AI frameworks, enabling data-driven decisions for platform optimization and next-generation hardware development.</p> <p>&nbsp;</p> <p><strong data-renderer-mark="true">In this position, your responsibility will be to:</strong></p> <ul> <li>Work closely with hardware, development teams to profile and analyze GPU performance at the system and kernel level.</li> <li>Evaluate and compare GPU performance across different platforms, architectures, and software stacks (e.g., CUDA, ROCm).</li> <li>Perform <strong data-renderer-mark="true">acceptance testing</strong> for new GPU clusters, ensuring hardware and software meet performance, stability, and compatibility requirements for AI workloads.</li> <li>Perform experiments across <strong data-renderer-mark="true">diverse GPU system configurations</strong> to assess the impact of varying interconnect strategies and system-level optimizations on performance and scalability.</li> </ul> <p>&nbsp;</p> <p><strong data-renderer-mark="true">We expect you to have:</strong></p> <ul> <li>Proficient in <strong data-renderer-mark="true">Unix/Linux</strong>, plus <strong data-renderer-mark="true">Python</strong> and <strong data-renderer-mark="true">Bash</strong> for automation.</li> <li>Good understanding of the GPU stack: CUDA,<strong data-renderer-mark="true">NCCL</strong>, drivers, and relevant libraries</li> <li>Proven ability to <strong data-renderer-mark="true">troubleshoot complex system issues</strong> including hardware, software, and networking problems.</li> <li>Familiarity with containerized environments (e.g., Docker, Kubernetes).</li> </ul> <p>&nbsp;</p> <p data-renderer-start-pos="1667"><strong data-renderer-mark="true">Ways to stand out from the crowd:</strong></p> <ul> <li data-renderer-start-pos="1426" data-local-id="cea6553d-9e7c-44c4-85b6-75dbae117e91">Experience with modern deep learning frameworks (PyTorch, JAX, vLLM, Tensort-LLM)</li> <li data-renderer-start-pos="1511" data-local-id="d887853a-b0d8-46d8-8110-6d7cb0ac9a9d">Experience with job schedulers and resource managers (<strong data-renderer-mark="true">Slurm, Volcano</strong>, etc.).</li> </ul><div class="content-conclusion"><p><strong>What we offer</strong>&nbsp;</p> <ul> <li>Competitive salary and comprehensive benefits package.</li> <li>Opportunities for professional growth within Nebius.</li> <li>Flexible working arrangements.</li> <li>A dynamic and collaborative work environment that values initiative and innovation.</li> </ul> <p><span data-contrast="auto">We’re growing and expanding our products every day. If you’re up to the challenge and are excited about AI and ML as much as we are, join us!</span></p></div>