Technical Product Manager - Soperator
About the role
About Nebius
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.
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.
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.
The role
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. We’re looking for a Technical Product Manager to own product direction for Soperator — our Slurm-on-Kubernetes control plane for GPU clusters. In this role, you will shape how ML engineers and research teams run, scale, and optimize distributed workloads in production. If you care about systems that combine performance, reliability, and developer experience at the frontier of AI infrastructure, this role is for you.
Your responsibilities will include:
- Own the full user journey across Soperator clusters: Slurm workflows, dashboards, alerts/notifications, node lifecycle, and training/inference capacity management.
- Define product direction end-to-end: problem discovery → solution design → delivery → adoption.
- Lead deep customer discovery through interviews, usage analytics, and workload analysis to uncover high-impact opportunities.
- Drive execution across platform teams: compute, networking, storage, observability, IAM and etc.
- Translate frontier ML and infrastructure ideas into practical product capabilities for real-world GPU clusters.
- Define success metrics, prioritize roadmap decisions with data, and ensure measurable customer/business impact.
- Lead the open-source strategy and execution for Soperator: shape public roadmap themes, prioritize OSS-facing capabilities, and ensure strong adoption in the community.
We expect you to have:
- 3–5+ years in Product Management, ML infrastructure/MLOps, distributed systems, or cloud platform engineering.
- Strong technical depth in distributed systems, cloud infrastructure, or ML platforms.
- Hands-on familiarity with large-scale ML training and orchestration tools (e.g., Slurm, Kubernetes, Ray).
- Track record of shipping technically complex products with multiple engineering teams.
- Strong communication and stakeholder management across engineering, research, and customers.
- Experience with product analytics, data-informed prioritization, and experimentation.
- High ownership, high learning velocity, and comfort operating in fast-moving AI infrastructure environments.
It will be an added bonus if you have:
- (Additional experience details not provided in the original posting.)