Jobs at Nebius

Develop and optimize GPU clusters and InfiniBand networks for hyperscale HPC environments. Responsibilities include troubleshooting hardware and infrastructure issues, integrating new GPUs through Kubernetes, QEMU, and KVM, managing GPU devices and InfiniBand fabrics, tuning performance, and improving automated monitoring and fault resolution.

Conduct frontier applied research on efficient AI model architectures, including sparse attention, long-context memory, selective computation, dynamic inference, reasoning, and continual adaptation. Formulate research questions, design rigorous experiments at meaningful scales, develop efficient implementations, publish findings, contribute to open-source tools and models, mentor researchers, and help direct the research stream.

Own the design, delivery, and operation of complex data pipelines, datasets, and platform components. Translate business needs into scalable data models and reliable data products, improve data quality and observability, resolve production issues, and establish reusable engineering tools and standards. Collaborate with product and business stakeholders, contribute to architecture decisions, mentor engineers, and participate in on-call support.

Lead the Managed Kubernetes Core team while remaining hands-on with backend engineering. Responsibilities include writing and reviewing code, leading technical projects, maintaining technical vision, participating in on-call and incident response, coaching 4–8 engineers, and collaborating on product strategy. The role focuses on Kubernetes control planes, cluster autoscaling, platform integrations, add-ons, GPU infrastructure, and managed cloud services.

Build and operate stateful streaming pipelines and Go services that process usage events into accurate, near-real-time billing data. Responsibilities include ingestion, validation, enrichment, pricing, storage integration, usage APIs, billing exports, failure recovery, idempotency, exactly-once processing, reconciliation, scalability, observability, and deployment ownership.

Maintain and scale DevTools SRE systems: improve user-facing developer workflows, build fault-tolerant self-healing architecture, optimize performance, modify open- and closed-source tools (GitLab, TeamCity), and support users while measuring improvements via metrics.

Manage end-to-end UK immigration cases and coordinate global immigration processes. Serve as primary contact for employees and stakeholders, ensure compliance with UK law, maintain case records in Jira and HiBob, liaise with external providers, and oversee invoice processing and governance to mitigate immigration risk.

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.

Build and scale AI-driven automation solutions using LLMs and agent frameworks. Design multi-step workflows, integrate AI with internal systems (HR, finance, legal, ticketing), automate document processing and data extraction, and train internal teams. Collaborate with technical leads, product, and IT to deliver practical, production-ready automation and iterate quickly.

Design and build the Capacity and Quota Management control plane for GPU resource allocation. Implement reservation engines, quota control algorithms, APIs, rebalancing, and auto-reclamation; ensure consistency, reliability, and scalable distributed backend services.

Design and build distributed backend services for the cloud monetization platform, focusing on correctness, consistency, scalable microservices, distributed transactions, and reliable asynchronous workflows. Influence system architecture, own service implementations, and collaborate across teams to support billing, reservations, payments, and revenue flows.

Build fault-tolerant, reliable cloud backend services for a hyperscaling AI platform, including compute, storage, networking, managed Kubernetes, databases, billing, monitoring and ML services.

Lead research on model architectures to improve attention, memory, and efficiency. Design and run experiments at scale, develop methods to reduce training/inference cost, collaborate with engineering for implementation, publish and open-source work, and mentor other researchers to shape the research direction.

The Senior Site Reliability Engineer will ensure fault-tolerance and uninterrupted operations, using innovative cloud technologies, alongside improving CI/CD processes.

Build and operate a managed PostgreSQL service for AI workloads: develop control plane and lifecycle automation in Go, tune PostgreSQL internals and ecosystem tooling, create migration tooling, integrate vector search, run SRE practices (SLOs, observability, incident response), and work directly with customers on architecture and escalations.