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.
Nebius is looking for a deeply technical Technical Product Manager – Storage to join the team. In this role, the candidate will own the vision, roadmap, and priorities for storage services in Nebius Cloud, including block storage, file and parallel file systems, object storage, and the storage capabilities that underpin AI/ML and HPC workloads.
The candidate will be responsible for shaping and managing backlogs for storage service teams and leading company-wide initiatives related to storage. This is a hands-on, technically demanding role: the candidate is expected to reason about storage internals, data paths, and performance trade-offs directly with engineers. It requires strong technical depth combined with the ability to coordinate across engineering, development, product, technical support, and go-to-market teams.
Responsibilities- Own and manage the product backlog for storage service teams (block, file, parallel/HPC, and object storage)
- Lead and coordinate cross-company initiatives involving storage, including data durability, performance, capacity, and cost initiatives
- Work closely with engineering and architecture teams to define product requirements at the level of data paths, consistency models, replication and erasure coding, and performance characteristics, and deliver new storage features
- Make informed technical trade-offs on durability, availability, latency, throughput, and cost, and defend them with data
- Partner with product marketing and technical pre-sales/post-sales teams on technical publications, go-to-market activities, customer engagement, acquisition, and retention related to storage
- Ensure the delivery of storage services that meet high standards for durability, availability, performance, scalability, and cost efficiency, including storage for AI/ML training and inference and HPC
- Hands-on experience building storage products in the cloud is the single most important requirement: the candidate must have designed, built, or operated cloud storage services (not just used or integrated them), in senior engineering, architecture, or technical leadership roles at hyperscalers, cloud providers, storage vendors, or other advanced technology companies
- Deep understanding of storage systems internals: block, file, and object storage architectures, distributed storage, replication and erasure coding, consistency and durability models, and the read/write data path
- Hands-on familiarity with technologies and interfaces such as NVMe/NVMe-oF, iSCSI, POSIX and parallel file systems (e.g., Lustre, GPFS/Spectrum Scale, BeeGFS), Ceph, S3-compatible object storage, and RDMA-based data paths
- Ability to reason quantitatively about IOPS, throughput, latency (including tail latency), and cost per usable TB, and to read and interpret benchmarks
- Strong technical expertise in at least two of the following areas:
- Block storage and virtualization (volumes, snapshots, replication, NVMe-oF)
- File and parallel file systems for HPC/AI (Lustre, GPFS, BeeGFS, NFS)
- Distributed storage internals (replication, erasure coding, consistency, repair)
- Storage performance engineering and benchmarking
- Object storage at scale (S3-compatible APIs, metadata, multipart, lifecycle)
- Proven track record of delivering complex technical initiatives requiring coordination across multiple teams or stakeholders
- Technical leadership experience is a strong plus
- Product management experience is not required, but a strong willingness to learn and grow into the role is essential
- Experience with storage for AI/ML training pipelines and large-scale HPC (checkpointing, data loading at scale, high-throughput sequential and random access patterns)
- Experience creating technical documentation, guides, tutorials, or reference architectures for storage products
The ideal candidate is a technically strong professional with a background in cloud or cloud storage products at hyperscalers (AWS, GCP, Azure), other public cloud providers, storage vendors, their partners, or highly digitalized enterprises.
The candidate may come from a background in storage engineering, distributed systems, architecture, SRE, or technical leadership, with hands-on experience building cloud storage services, distributed storage systems, or high-performance storage for ML and HPC. Experience in technical product or platform ownership or technical leadership is highly valued, even if the candidate has not held a formal manager title.
Relevant experience in ML and HPC environments is strongly desirable given the storage demands of these workloads, though the candidate is expected to adapt quickly and learn new domains.
About Nebius
Nebius AI is an AI cloud platform with one of the largest GPU capacities in Europe. Launched in November 2023, the Nebius AI platform provides high-end, training-optimized infrastructure for AI practitioners. As an NVIDIA preferred cloud service provider, Nebius AI offers a variety of NVIDIA GPUs for training and inference, as well as a set of tools for efficient multi-node training.
Nebius AI owns a data center in Finland, built from the ground up by the company’s R&D team and showcasing our commitment to sustainability. The data center is home to ISEG, the most powerful commercially available supercomputer in Europe and the 16th most powerful globally (Top 500 list, November 2023).
Nebius’s headquarters are in Amsterdam, Netherlands, with teams working out of R&D hubs across Europe and the Middle East.
Nebius AI is built with the talent of more than 500 highly skilled engineers with a proven track record in developing sophisticated cloud and ML solutions and designing cutting-edge hardware. This allows all the layers of the Nebius AI cloud – from hardware to UI – to be built in-house, distictly differentiating Nebius AI from the majority of specialized clouds: Nebius customers get a true hyperscaler-cloud experience tailored for AI practitioners. 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!
Benefits & Perks:
- Competitive compensation
- Career growth and learning opportunities
- Flexibility and ownership
- Collaborative and innovative culture
- Opportunity to work on impactful AI projects
- International environment and talented teams
What's it like to work at Nebius:
Fast moving - Bold thinking - Constant growth - Meaningful impact - Trust and real ownership - Opportunity to shape the future of AI
Equal Opportunity Statement:
Nebius is an equal opportunity employer. We are committed to fostering an inclusive and diverse workplace and to providing equal employment opportunities in all aspects of employment. We do not discriminate on the basis of race, color, religion, sex (including pregnancy), national origin, ancestry, age, disability, genetic information, marital status, veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by applicable law.
Applicants must be authorized to work in the country in which they apply and will be required to provide proof of employment eligibility as a condition of hire.
If you need accommodations during the application process, please let us know.
Skills Required
- Hands-on experience designing, building, or operating cloud storage services (cloud providers, hyperscalers, storage vendors, or advanced tech companies)
- Deep understanding of storage systems internals: block, file, object architectures, distributed storage, replication, erasure coding, consistency and durability models, and read/write data paths
- Hands-on familiarity with NVMe/NVMe-oF, iSCSI, POSIX, NFS, parallel file systems (Lustre, GPFS/Spectrum Scale, BeeGFS), Ceph, S3-compatible object storage, and RDMA-based data paths
- Ability to reason quantitatively about IOPS, throughput, latency (including tail latency), and cost per usable TB and interpret benchmarks
- Strong technical expertise in at least two areas: block storage/virtualization, file/parallel file systems, distributed storage internals, storage performance engineering/benchmarking, object storage at scale
- Proven track record delivering complex technical initiatives across multiple teams or stakeholders
- Willingness to learn and grow into product management (product management experience not required)
- Technical leadership experience
- Experience with storage for AI/ML training pipelines and large-scale HPC (checkpointing, data loading at scale)
- Experience creating technical documentation, guides, tutorials, or reference architectures for storage products
What We Do
Cloud platform specifically designed to train AI models
