Technical Product Manager - Soperator
Nebius - Amsterdam, Netherlands; Berlin, Czech Republic; Remote - Europe - Salary not disclosed
Sponsored
Job description
<div class="content-intro"><p><strong>About Nebius:</strong></p> <p>Nebius is leading a new era in cloud infrastructure for the global AI economy. We are building a full-stack AI cloud platform that supports developers and enterprises from data and model training through to production deployment, without the cost and complexity of building large in-house AI/ML infrastructure.</p> <p>Built by engineers, for engineers. From large-scale GPU orchestration to inference optimization, we own the hard problems across compute, storage, networking and applied AI.</p> <p>Listed on Nasdaq (NBIS) and headquartered in Amsterdam, we have a global footprint with R&D hubs across Europe, the UK, North America and Israel. Our team of 1,500+ includes hundreds of engineers with deep expertise across hardware, software and AI R&D.</p></div><p><strong><span data-ccp-props="{}">The role</span></strong></p> <p>At Nebius, we’re building a next-generation AI compute platform for large-scale ML training and inference — from a few nodes to thousands of GPUs.<br>We’re looking for a <strong>Technical Product Manager</strong> to own product direction for <strong>Soperator</strong> — our Slurm-on-Kubernetes control plane for GPU clusters.<br>In this role, you will shape how ML engineers and research teams run, scale, and optimize distributed workloads in production.<br>If you care about systems that combine <strong>performance, reliability, and developer experience</strong> at the frontier of AI infrastructure, this role is for you.</p> <p><strong><span data-contrast="auto"><span data-ccp-charstyle="Strong">Your responsibilities will include:</span></span></strong><span data-ccp-props="{"134233117":true,"134233118":true}"> </span></p> <p><span data-contrast="auto"><span data-ccp-parastyle="Normal (Web)">• Own the full user journey across Soperator clusters: Slurm workflows, dashboards, alerts/notifications, node lifecycle, and training/inference capacity management.<br>• Define product direction end-to-end: <strong>problem discovery → solution design → delivery → adoption</strong>.<br>• Lead deep customer d