Tech Stack

Description

You will own the product direction for Soperator, Nebius's Slurm-on-Kubernetes control plane for GPU clusters. Your role involves shaping how ML engineers run, scale, and optimize distributed workloads in production, from problem discovery to delivery and adoption.

Requirements

• 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
• Experience with product analytics, data-informed prioritization, and experimentation

Responsibilities

• Own full user journey across Soperator clusters: Slurm workflows, dashboards, alerts, node lifecycle, capacity management
• Define product direction end-to-end: problem discovery to delivery and adoption
• Lead customer discovery through interviews, usage analytics, and workload analysis
• Drive execution across platform teams: compute, networking, storage, observability, IAM
• Lead open-source strategy and execution for Soperator