Technical Product Manager - Robotics

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 We're hiring a Senior Product Manager for Physical AI to own the PM craft end-to-end — customer discovery, requirements, roadmap, prioritization, launch, cross-functional execution — for the first generation of Physical AI cloud products on Nebius. You'll partner closely with our Field CTO , who leads the vertical strategic direction and external narrative, while you ship the product that puts that strategy into the world. You'll spend your time deep in the Physical AI stack (simulation, synthetic data, robot learning, sim-to-real) and in front of robotics, AV, and industrial automation customers. What success looks like in 12 months: You've talked to 20+ Physical AI companies and research labs and built the customer-evidence base that you and the Field CTO use to refine the Physical AI strategy. You've shipped the first Physical AI-specific solution packages alongside engineering — running real customer workloads, with measurable usage. You've stood up the Physical AI product cadence — planning, prioritization, customer review — and it's running. You've translated complex Physical AI workflows (simulation → training → eval → deploy) into a prioritized backlog and concrete requirements the platform and infrastructure teams are executing against. You're the senior product partner the Field CTO works with on strategy refinement, technical collateral, reference architectures, and demo material — co-authoring the docs, jointly carrying the customer narrative. 2–3 strategic partnership / co-development opportunities have been identified, qualified, and handed off to the Field CTO and BD for closing. What you'll own: Product execution (yours to lead) Drive the Physical AI roadmap Translate Physical AI workflows (sim, synthetic data, robot learning, digital twins, sim-to-real) into requirements platform and infra teams build against. Customer discovery Run discovery and prototype validation with technical leaders at robotics, AV, industrial automation, and research labs. Maintain the Physical AI customer-insight base; feed it into the roadmap and the strategy refresh you do with the Field CTO. Strategy partnership Co-shape Physical AI strategy: where we play, how we segment, what we prioritize. Write the memos, segment analyses, and evidence packs that ground it. Bring your own POV; align with the Field CTO as the final external voice. GTM enablement Build the technical collateral, reference architectures, and demos that Sales, Solutions Engineering, and the Field CTO use in the field. Represent Nebius at Physical AI / robotics venues (GTC, ROSCon, ICRA, CoRL) as the senior product voice alongside the Field CTO. Cross-functional leadership Drive alignment across engineering, Applied AI / SE, marketing, sales, and BD without direct authority. Coordinate with adjacent product teams (Serverless, MLOps, Marketplace) so Physical AI requirements show up in their roadmaps. What we're looking for: Senior PM craft. You can run a product area as a senior IC: write a crisp PRD, build and defend a roadmap, run a clean prioritization meeting, ship to a deadline, and unblock a cross-functional team without escalating. You've done this before, ideally in cloud / AI infra / robotics. Deep technical fluency in the Physical AI stack. Isaac Sim, MuJoCo, Gazebo, Unreal/Unity for sim. Synthetic data generation and domain randomization. RL and imitation learning for robot policies. Sim-to-real transfer. Sensor simulation (LiDAR, camera, IMU), annotation pipelines, dataset management at scale. Working knowledge of GPU-accelerated training and simulation workloads — multi-node distributed training, MLOps, experiment tracking applied to robot learning. Strong customer instinct. You can run a discovery call with a robotics CTO and walk out with the right requirements, not the requirements they asked for. You can read a market and tell us where we should be playing. What your background probably looks like: 5+ years of product management, ideally with at least one stint owning a product area or major workstream end-to-end at a cloud provider, AI infrastructure company, GPU computing platform, or P