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Lead and coordinate large-scale cloud platform programs across many teams, set goals and timelines, drive technical and procedural decisions, introduce reproducible processes, and align stakeholders up to C-level to scale regions and hardware generations.

Serve as primary technical advisor for strategic GPU cloud customers, guiding design, deployment, and scaling of large-scale ML training and inference workloads. Troubleshoot complex AI/ML issues, optimize GPU performance, liaise with sales and product teams, and drive customer-aligned feature requests and solutions.

Lead planning and execution for External Solutions, coordinating multi-team engineering and product efforts to launch external-facing cloud services. Align Sales, Partnerships, Legal, and engineering stakeholders, manage deployments to datacenters, structure programs, and drive delivery for managed services, integrations, and serverless offerings.

Own the vision and backlog for Nebius storage services (block, file, parallel/HPC, object). Define technical requirements (data paths, consistency, replication, erasure coding), make performance/durability trade-offs, coordinate cross-team initiatives, and ensure storage meets durability, availability, scalability, and cost targets for AI/ML and HPC workloads.

Lead development of data center and AI infrastructure projects from executed agreement through construction readiness. Own roadmaps, schedules, budgets, risk registers, permitting, utility coordination, and stakeholder alignment. Deliver development-ready projects to Delivery with complete documentation, readiness gates, and minimized risk while building repeatable standards and governance for future projects.

Drive complex VPC and cloud-networking programs from goals to production: define outcomes, expose dependencies, manage risks and schedules, coordinate cross-team delivery, validate rollouts, and ensure operational readiness.

Manage server and rack-level production projects for AI datacenter infrastructure, overseeing procurement, vendor coordination, and logistics for timely deployment.

Nebius seeks a Senior ML Engineer for AI R&D focusing on applied research in reinforcement learning and agent training, requiring deep expertise in machine learning and software engineering.

The Site Selection & Colocation Manager oversees site selection for data centers, involving market analysis, due diligence, vendor management, and cross-functional collaboration.

Serve as the technical partner interface to design, build, and maintain integrations and reference implementations between Nebius and strategic partners. Architect enterprise-ready solutions for GPU-accelerated AI/ML workflows, enable partner teams with docs and demos, influence product roadmap, and provide technical leadership for complex joint deployments and troubleshooting.