The Role

We’re looking for a Network Software Engineer (NetSWE) to build software that makes network operations safe, scalable, and boring — even as we launch new data centers and expand fast. This is not a “write scripts for configs” role: you’ll build the tooling and services that sit between the network core (switches/ports/VLANs, traffic processors) and the cloud platform on top, using open source where it fits and building the missing pieces where it doesn’t.

Your responsibilities will include:

• Build and maintain services and tooling that automate the network lifecycle: day-0 provisioning, day-N changes, drift detection, and operational verification

• Make network changes safe and transparent: CI/CD workflows, diff/review tooling, staged rollouts/rollbacks, audit trails, and guardrails

• Develop observability systems that scale across many sites: telemetry pipelines, signal quality, and tooling that shortens incident investigations

• Close “last mile” gaps between the network and the platform: integrate source-of-truth data, expose APIs, and build reliable automation around it

• Collaborate closely with network engineers and SREs to turn real operational pain into product-quality tooling

We expect you to have:

• 5+ years of professional software engineering experience (or equivalent practical background)

• Strong coding skills and ownership mindset: you can ship and operate reliable services

• Proficiency in Go or readiness to switch; Python is also welcome (other languages can be useful for OSS debugging/fixes)

• You don’t have to be Network expert but we expect you to have interest in infrastructure and/or network

It will be an added bonus if you have:

• Background in networking (ex-network engineer, CCNP/education, DC networking exposure) or strong interest and proven ability to learn fast

• Experience building automation/infra tooling: CI/CD, IaC, testing/staging environments, or “network-as-code” style workflows

• Low-level networking / datapath experience: eBPF/XDP, DPDK, kernel networking, traffic processing systems

• Experience designing high-load services and observability platforms (metrics/logs/traces, alerting, regression detection)

• Contributions to open source or experience extending/debugging OSS components in production environments

Nebius Managed Kubernetes (mk8s) mission is to grow the Nebius cloud platform by providing a Kubernetes-native way to run AI systems with high efficiency and low operational overhead.
With a single click, it provides a Kubernetes cluster on top of Nebius services for compute (VMs) and networking.
In 2026, the service is scaling 10× and is expected to manage customer workloads across tens of thousands of GPU servers in more than 10 data centers.

You will lead the mk8s Core team, one of three mk8s teams. The Core team owns the API, the core of the service control plane, cluster autoscaling, platform integrations, and running k8s add-ons.

At Nebius, team leads are hands-on. We expect you to be a senior or staff engineer now (or earlier in your career). You will start as an individual contributor to gain context, then take on managerial responsibilities.

In this position, you will be responsible to:

• Lead by example. Set the quality bar by spending a significant portion of your time on IC work: writing and reviewing code, leading projects, and participating in on-call rotation, incident mitigation, and post-incident analysis.
• Manage 4–8 mid-to-senior engineers. Provide context, coach, and give regular feedback.
• Maintain the technical vision for your area of responsibility.
• Collaborate with the Product Manager and Service Owner to shape product vision and plans.

Examples of outcomes you could drive as a Team Lead

• Optimize the service control plane to create and manage 20K GPU nodes in a single Kubernetes cluster, enabling a major contract for the company.
• Integrate cluster autoscaling approaches (e.g., Karpenter) to improve resource utilization and support seamless auto-upgrades.
• Provide a Kubernetes-native way to use local disks to reduce disk I/O bottlenecks for AI training and inference, improving efficiency.
• Deliver managed Layer 7 load balancers to reduce operational overhead for customers.

What you will bring to the table:

• 8+ years of professional software engineering or management experience
• Excellent knowledge of Golang, or you are ready to quickly switch to this programming language
• Expertise with
• Multi-month technical projects
• Tech leading engineers
• Owning multi-month technical projects.

It would be an added bonus if you had:

• Experience with Team management, Kubernetes administration, Developing Kubernetes controllers

• Serverless AI has clear product-market fit with measurable activation and retention metrics improving quarter over quarter.
• Multi-node jobs and autoscaling endpoints are shipped and adopted by customers running production workloads.
• Cold start time is reduced from 1-3 minutes to under 60 seconds for common workloads through a combination of product and infrastructure improvements you drove.
• Developer experience (CLI, docs, error messages, onboarding flow) sets the standard that developers expect from a next-generation AI cloud.
• At least 3 product decisions you made are directly attributable to customer conversations or data analysis you conducted.

• Co-own the Serverless AI product roadmap — Jobs, Endpoints, and DevPods — taking primary ownership of specific product areas while collaborating closely with the other PM on shared priorities and cross-cutting decisions.
• Write detailed, technically precise PRDs that engineering teams can execute against. Our PRDs specify CLI syntax, API contracts, state machines, and billing models — not abstract feature descriptions.
• Make build/buy/defer decisions on capabilities like autoscaling, multi-node orchestration, HTTPS termination, secret injection, and health checking based on customer signal and strategic priorities.

• Understand the full workload lifecycle: container image pull → VM provisioning → GPU attachment → workload execution → cleanup — well enough to identify bottlenecks and propose solutions.
• Evaluate technical trade-offs in areas like container cold start optimization (image caching, snapshot restore, warm pools), GPU scheduling and bin-packing, and storage mount performance.
• Work directly with engineers on architecture decisions for distributed training support, endpoint autoscaling policies, and fault tolerance mechanisms.
• Stay current on the fast-moving serverless GPU infrastructure space — new inference frameworks (vLLM, TensorRT-LLM, SGLang), container runtimes, orchestration approaches — and translate trends into product direction.

• Run customer discovery and feedback sessions with ML engineers and platform teams at AI startups and enterprises. Turn qualitative insight into specific product actions.
• Analyze usage data, activation funnels, and churn patterns to identify where users get stuck and what features drive retention.
• Track market dynamics, emerging technologies, and industry trends to inform product strategy and ensure Nebius stays ahead of where the market is heading.
• Define and iterate on pricing, packaging, and tier strategy for Serverless AI.

• Own the technical content strategy: quickstart guides, tutorials, reference architectures, and example workloads that reduce time-to-first-job.
• Partner with marketing on developer-focused campaigns, webinars, and conference presence.
• Work with Solution Architects and Sales to qualify serverless-fit opportunities and support technical evaluations.

• You have built, shipped, and iterated on infrastructure or platform products used by developers or ML engineers. Not consumer apps. Not dashboards. Infrastructure.
• You understand containers at a practical level — Docker, image registries, container runtimes, resource limits, networking. You've debugged why a container won't start, why GPU isn't visible inside it, or why a mount isn't working.
• You have working knowledge of GPU computing for AI/ML: what GPU types exist and when to use them, how training and inference workloads differ in resource requirements, what vLLM / TensorRT-LLM / Triton are and why they matter.
• You can read a CLI reference and know if it's well-designed. You've shaped developer-facing APIs, CLIs, or SDKs.
• You have run real customer discovery — not surveys, but technical conversations with engineers where you learned something that changed your product direction.
• You have 3+ years of product management experience in cloud infrastructure, AI/ML platforms, or developer tools.

• Ability to whiteboard a workload lifecycle (submit → schedule → provision → execute → cleanup) and identify failure modes at each step.
• Understanding of autoscaling trade-offs: scale-to-zero vs. warm pools, scaling metrics (queue depth, latency, utilization), cold start implications.
• Familiarity with inference serving concepts: batching, model loading, quantization, KV-cache management, multi-model serving.
• Understanding of distributed training concepts: data parallelism, model parallelism, communication overhead, checkpointing.
• Ability to reason about pricing models: per-second vs. per-request vs. per-token, and how pricing interacts with product architecture.

• Experience at a serverless or GPU cloud company.
• Hands-on ML engineering background — you've trained models, deployed inference endpoints, or built ML pipelines yourself.
• Experience with Kubernetes for ML workloads (Kubeflow, KServe, Ray Serve) and understanding of why many ML teams want to avoid it.
• Prior experience building a product from early stage to scale in a fast-growing market.
• Background in systems engineering, distributed systems, or site reliability engineering.

• You are more comfortable in a terminal than in a slide deck.
• You form strong opinions based on data and direct customer signal, and you update them when evidence changes.
• You are energized by building at pace — small team, fast-evolving product, big opportunity.
• You care about developer experience at the level of error messages, CLI flag naming, and documentation quality.
• You'd rather ship a smaller thing that works perfectly than a bigger thing that's mediocre.

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!

Summary:

Location: Amsterdam
Duration: 3 months
Start date: June 2026 
Compensation: Paid
Eligibility: Current University student (Computer Science or related field), Recent Graduate or Early Career specialist
Work authorization: Permitted to work in the job’s location

The role

You’ll work alongside experienced engineers, learn how high-performance backend systems are designed and operated and contribute code that runs in real environments used by customers worldwide. You’ll get hands-on experience with modern backend technologies, scalable architectures and engineering best practices in a team that works at the cutting edge of AI cloud infrastructure.

We expect you to have:

• Knowledge of at least one programming language (Go, Java, Python or С++).
• Understanding of basic algorithms and data structures.
• Strong motivation to learn, grow and develop as a backend engineer.
• Willingness to work with complex systems and ask questions.

What we offer:

• Competitive salary and comprehensive benefits package.
• Mentorship from experienced AI, ML, and cloud infrastructure professionals.
• Hands-on experience with real customer workloads and production systems.
• Opportunities for professional growth within Nebius.
• A dynamic and collaborative work environment that values initiative and innovation.
• Opportunity to be considered for a full-time role after the Early Talent Program.

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!

Summary:

Location: Amsterdam
Duration: 3 months
Start date: June 2026 
Compensation: Paid
Eligibility: Current University student (Computer Science or related field), Recent Graduate or Early Career specialist
Work authorization: Permitted to work in the job’s location

Why work at Nebius
Nebius is leading a new era in cloud computing to serve the global AI economy. We create the tools and resources our customers need to solve real-world challenges and transform industries, without massive infrastructure costs or the need to build large in-house AI/ML teams. Our employees work at the cutting edge of AI cloud infrastructure alongside some of the most experienced and innovative leaders and engineers in the field.

Where we work
Headquartered in Amsterdam and listed on Nasdaq, Nebius has a global footprint with R&D hubs across Europe, North America, and Israel. The team of over 1400+ employees includes more than 400 highly skilled engineers with deep expertise across hardware and software engineering, as well as an in-house AI R&D team.

Your responsibilities will include

• Operation:
  • assist, where possible in day-to-day SRE operations tasks in NetInfra
  • deploy tested and approved changes following clear instructions
• Project work:
  • execute small and well-defined tasks from the backlog
  • together or instead: work on small and well-defined SRE project from backlog
  • create tests for their changes/project (if applicable)
  • write technical documentation about their work
  • track and update Jira tasks according to their progress
• Learning and growth:
  • actively study network and system fundamentals: Ethernet and ip networks, routing, Linux Kernel, eBPF, traffic control, ipvs, dpdk
  • learn internal tools, workflows and operational standards
  • learn container and platform fundamentals: Kubernetes (core architecture and networking), Helm, Terraform
  • learn configuration management and automation basics

• demonstrate strong interest and foundational knowledge in cloud providers, operations, networking, hardware, and software
• programming experience in any of Python, Go or C++
• basic understanding of the Network (ethernet, ip, tcp/udp, routing fundamentals)
• familiarity with Git
• basic understanding of containers, Kubernetes and IAC (Infra As Code) approach

What we offer

• Competitive salary and comprehensive benefits package
• Mentorship from experienced AI, ML, and cloud infrastructure professionals
• Hands-on experience with real customer workloads and production systems
• Opportunities for professional growth within Nebius
• A dynamic and collaborative work environment that values initiative and innovation
• Opportunity to be considered for a full-time role after the Early Talent Program

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!

The Product

In a rapidly evolving world, trust in AI depends on AI agents being grounded in fresh, verified real-world data. Search is the foundation that makes this possible.

We are building an agent-native search platform designed specifically for AI systems rather than human users. Our product provides programmatic, low-latency, and observable search APIs that AI agents use to retrieve, filter, and reason over real-world information at scale.

The Role

We are looking for a Senior Software Engineer to work on the indexing and data processing layer of a novel search engine tailored for agentic AI consumption.

In this role, you will focus on building systems that ingest, process, and organise massive volumes of data into efficient, queryable structures. You will work primarily on offline and nearline pipelines, ensuring that data is fresh, complete, and efficiently accessible by downstream retrieval systems. You will operate in an environment where throughput, scalability, and correctness are critical — designing systems capable of handling tens of gigabytes per second across continuously evolving datasets.

In this position, your responsibility will be to

• Design, implement, and operate large-scale indexing systems and data pipelines that sit at the core of our search infrastructure
• Build ingestion workflows for internal and external data sources, including web-scale crawling and structured feeds
• Develop and optimise indexing strategies balancing performance, freshness, and resource efficiency
• Work on storage formats, compaction strategies, and update mechanisms to keep data accessible and current
• Ensure reliability and predictability of pipelines under high-throughput conditions
• Build well-tested components with clear responsibilities and interaction contracts, while remaining flexible as the system evolves
• Define and implement observability primitives, including structured logs, metrics, and data quality signals across offline and nearline pipelines
• Monitor throughput, resource usage, and cost, and drive optimisations when business needs require it
• Collaborate with runtime and ML teams to ensure indexing outputs meet retrieval and ranking requirements
• Enable safe experimentation on indexing strategies and data processing logic through controlled rollouts and clearly defined quality signals

You may be a good fit if you:

• Have 5+ years of experience building production backend or data systems
• Have strong hands-on experience with Go in real-world, high-load services (experience with other systems languages such as C++ or Rust is a plus)
• Have worked on systems at significant scale — such as 10k+ RPS or 10+ GiB/sec throughput
• Have experience building or operating databases, data planes, or large-scale data pipelines
• Understand distributed systems fundamentals, including fault tolerance, failure modes, and horizontal scalability
• Have operated your own systems in production: handled incidents, made real-world tradeoffs, and understand what running data infrastructure at scale truly involves
• Think in terms of systems and data flows rather than isolated components, reasoning end-to-end about how data moves through the stack
• Can make pragmatic decisions under pressure without compromising long-term system health
• Collaborate effectively across infrastructure, ML, and product teams, communicating clearly in cross-functional settings

Strong candidates may also have experience with:

• Distributed data processing frameworks such as Spark, Flink, MapReduce, or Beam
• Content systems including web crawling, scraping, proxying, or anti-bot infrastructure
• Ad tech, social networks, or other large-scale content platforms
• DBMS internals (open source or SaaS) and cloud infrastructure
• Open-source contributions or active involvement in the engineering community
• Competitive programming or CTF participation (ICPC, IOI, or similar)
• SHAD or similar advanced technical programmes
• Conference talks or technical publications

We conduct coding interviews as part of the process.

The role

We’re looking for a Backend Engineer to contribute to the development of our hyperscaler platform.

Your responsibilities will include:

Develop fault-tolerant, reliable cloud services: cloud infrastructure, managed databases, managed Kubernetes, billing, monitoring systems, ML service and more.

We expect you to have: 

• 5+ years of professional software engineering experience;
• Knowledge of C++ programming language;
• Knowledge of Python, Java, and Go is a plus;
• Ability to write reliable code and dig into complex problems;
• Teamwork-oriented approach;
• Fluency in English.

Nice to have:

Experience designing high-load and scaling services.

We conduct coding interviews as part of the process.

We are looking for a Senior Systems HPC Engineer to play a key role in building our hyperscaler platform, working across its core components while analyzing and optimizing the performance of large-scale GPU clusters at the intersection of hardware and software.

You will operate across the full stack—from hardware and system software to networking (InfiniBand/RoCE), virtualization (KVM/QEMU), and distributed communication layers (e.g., MPI, NCCL).

In this role you will

• Focus on understanding system behavior across multiple layers, identifying performance bottlenecks, and driving improvements that shape how our clusters are built, operated, tuned, and validated.
• Investigate and troubleshoot performance issues of GPU cluster under real workloads (training and inference)
• Evaluate and integrate new hardware, system configurations and tuning approaches through software stack
• Support complex performance-related escalations from internal teams and customers
• Work closely with infrastructure, software engineering and hardware vendor teams (e.g. NVIDIA, Mellanox, Intel)
• Contribute to hardware and cluster qualification (acceptance), ensuring systems meet performance expectations

We expect you to have:

• 5+ years of professional experience in system-level software development (focused on performance optimization, low-level programming).

• 3+ years of hands-on experience with Linux systems (administration, troubleshooting, and performance tuning).

• In-depth understanding of server architecture, including PCIe devices, NICs, Linux OS/Kernel, and high-performance computing (HPC) systems.

• Strong proficiency in one or more performance-oriented programming languages (C/C++, Go, Python).

We conduct coding interviews as part of the process.

The role

The VPC (Virtual Private Cloud) team builds and operates the core networking layer of our cloud platform. We enable virtual machines to communicate reliably by abstracting them from the underlying physical network, providing seamless IP-based connectivity even as workloads move across the datacenter.

Our team designs secure, isolated private networks for customers, connects them to the public internet, and delivers essential networking services such as load balancers, firewalls, and security groups. Because nearly every cloud application depends on networking, VPC is a foundational service for the entire platform.

Stability and resilience are our top priorities—we engineer systems to remain reliable and operational even when parts of the cloud experience failures.

What we do:

• Increase service scalability
• Developing service functionality (e.g. IPv6 support, service endpoints, VPC peering, L7 load balancers and other networking services)
• Improve the internal architecture, optimizing interaction with related services 

In this position, your responsibility will be to:

• Develop control & data plane for Nebius Cloud network services
• Improve service performance and reliability
• Automate complex cross-service interaction scenarios
• Perform load testing for services

We expect you to have:

• Capable of writing reliable, high-performance code
• Proficient in C/C++ or Go and ready to learn both.
• Familiar with routing network traffic

It would be an added bonus if you had:

• Worked with VPP, DPDK, and the Linux kernel network subsystem
• Well-versed in virtual networks and overlays, SDN, NFV, DPI, network protocols, routing and tunneling, BGP, and MPL

We conduct coding interviews as part of the process.

Nebius is looking for a Senior Technical Recruiter to strengthen our Talent Acquisition team and help us attract top technical talent. In this role, your primary focus will be on active sourcing and building strong pipelines of backend engineers, system engineers, and technology experts to support the company’s continuous growth.

Remote working, Based in the UK (London) OR Netherlands, working Hybrid from Amsterdam.

Your responsibilities will include:

• Technical Talent Sourcing: Proactively identify and engage engineers and other tech specialists through diverse channels (LinkedIn, GitHub, Boolean Search, professional communities, conferences, forums, networking, employee referrals).

• Pipeline Development: Build, maintain, and continuously refresh a pool of qualified engineers and developers for current and future hiring needs; provide funnel statistics to Hiring Managers (e.g., number of applicants, time to hire, etc.).

• Candidate Engagement: Craft personalized outreach and communication to spark interest and showcase opportunities at Nebius. Engage in pre-onboarding activities and contribute to HR projects.

• Screening: Conduct resume reviews and initial calls to assess candidates’ technical background, experience, and motivation.

• Collaboration with Hiring Managers: Partner with engineering leaders to deeply understand role requirements and design effective sourcing strategies.

• Market Research & Insights: Stay on top of industry trends, tech community activity, and competitor hiring practices. Identify the best companies to target for top-tier technical talent.

We expect you to have:

• 4+ years of experience in technical recruitment, specializing in Backend/General Tech such as (but not limited too): Software Engineers, Python Engineers, Platform Engineers, Cloud Platform Engineer, Site Reliability and Infrastructure Engineers, DevOps, Systems Engineers and Data Platform Engineers.

• Strong sourcing expertise and familiarity with tech talent pools, platforms, and communities.

• Deep understanding of tech subject areas, developers’ roles, technologies, and motivations, plus insight into which companies are the best sources of top candidates.

• Ability to manage multiple priorities and work in a fast-paced environment.

• Excellent follow-through, organizational, presentation, and communication skills (both written and verbal).

• Creative problem-solving skills with the ability to adapt quickly.

About the role:

Token Factory is a part of  Nebius Cloud, one of the world’s largest GPU clouds, running tens of thousands of GPUs. We are building an inference platform that makes every kind of foundation model — text, vision, audio, and emerging multimodal architectures — fast, reliable, and effortless to deploy at massive scale.

Responsibilities:

• Develop and optimize low-level kernels and runtime components for AI inference 

• Improve performance of inference engines GPU platforms 

• Profile and debug system-level and hardware-level performance issues 

• Integrate support for new hardware architectures (Hopper, Blackwell, Rubin) 

• Collaborate with ML and backend teams to optimize end-to-end execution 

Required Qualifications:

• Strong proficiency in C++, OR expertise in GPU programming with a focus on low-level high-performance coding and memory management 

• Experience in GPU programming or systems-level software development, e.g. operating system internals, kernel modules, or device drivers 

• Hands-on experience with profiling and debugging tools to identify performance issues on both CPUs and GPUs, and the ability to optimize code based on those findings. 

• Solid understanding of CPU/GPU architecture and memory hierarchy 

Preferred Qualifications: 

• Experience with GPU computing programming: CUDA, ROCm, CUTLASS, Cute, ThunderKittens, Triton, Pallas, Mosaic GPU 

• Familiarity with ML inference runtimes (e.g. TensorRT, TVM) 

• Knowledge of Linux internals, drivers, or compiler toolchains 

• Experience with tools like perf, VTune, Nsight, or ROCm profiler 

• Familiarity with popular inference engines (e.g. such as vLLM, sglang, TGI) 

We conduct coding interviews as part of the process.

The role

We’re looking for a Senior HPC Cluster Engineer to join our team and play a key role in the development of our cutting-edge hyperscaler platform. The GPU & InfiniBand team is responsible for enhancing and optimizing the core components of our Cloud platform, with a specific focus on GPU computing, InfiniBand networks, and the KVM/QEMU stack. You’ll work closely with hardware virtualization and device emulation technologies, ensuring high performance and security in multi-GPU, HPC environments. The role involves analyzing, troubleshooting, and improving infrastructure to support new hardware, fine-tuning system performance, and automating fault detection and resolution in a complex system.

In this position, you will be responsible for:

• Tuning the performance of GPU clusters and InfiniBand networks to ensure optimal operation in HPC and GPU-based environments.

• Analyzing and troubleshooting the root cause of issues related to GPUs and InfiniBand networks, and proposing corrective actions.

• Integrating new hardware into the existing infrastructure, including support for new GPU hardware through software stacks like Kubernetes, QEMU, and KVM.

• Enhancing automation systems for proactive monitoring, detecting, and resolving issues in GPU and InfiniBand environments.

• Configuring and managing GPU devices and InfiniBand fabrics, ensuring efficient and reliable operation.
  

We expect you to have:

• 5+ years of professional experience in system-level software development (focused on performance optimization, low-level programming).

• 3+ years of hands-on experience with Linux systems (administration, troubleshooting, and performance tuning).

• In-depth understanding of server architecture, including PCIe devices, NICs, Linux OS/Kernel, and high-performance computing (HPC) systems.

• Strong proficiency in one or more performance-oriented programming languages (C/C++, Go, Python).

It would be a plus if you have:

• Experience with GPU end-to-end testing in a cluster environment using InfiniBand networking.

• Proven track record of analyzing and optimizing the performance of HPC workloads (e.g., simulations, data analysis, AI/ML workloads).

• Familiarity with RDMA, RoCE, and InfiniBand protocols for high-performance communication.

• Background in Software-Defined Networking (SDN) and experience with HPC cluster networking.

• Understanding of QEMU/KVM virtualization and managing virtualized environments.

• Experience with deep learning frameworks such as PyTorch and TensorFlow, and their integration with HPC systems.

• Familiarity with collective communication libraries like MPI and NCCL for distributed computing. 

We conduct coding interviews as part of the process.

The role

This role is for Nebius AI R&D, a team focused on applied research in AI. Examples of applied research that we have recently published include:

• applying reinforcement learning for agent training in long-context multi-turn scenarios
• dramatically scaling task data collection to power reinforcement learning for SWE agents
• building a decontaminated evaluation for SWE agents that is regularly updated
• investigating how test-time guided search can be used to build more powerful agents

The results often lead to collaboration with adjacent teams where our research findings are applied in practice.

We are currently looking for senior- and staff-level ML engineers to work on research in areas such as:

• Guided search and reinforcement learning for agentic systems
• Reinforcement learning for reasoning models
• Web-scale problem collection for training agents
• Efficient model distillation

Some examples of what your responsibilities might include are:

• Conducting experiments to figure out efficient ways to train a large language model on traces of interactions with various environments
• Exploring methods of guided generation and search in the trajectory space
• Coming up with ways to mine relevant data at web scale and figuring out efficient ways to use this data in model post-training
• Conducting experiments with different reinforcement learning configurations in verifiable domains
• Exploring methods to train AI agents on tasks with non-verifiable reward signals

We expect you to have:

• A profound understanding of theoretical foundations of machine learning and reinforcement learning
• Deep expertise in modern deep learning for language processing and generation
• Substantial experience with training large models on multiple computational nodes
• Strong software engineering skills (we mostly use python)
• Deep experience with modern deep learning frameworks (we use jax)
• Strong communication and leadership abilities
• Experience designing, executing, and analyzing machine learning experiments with proper statistical rigor
• Ability to formulate research questions, design experiments to test hypotheses, and draw meaningful conclusions from results
• Ability to document research findings clearly and contribute to technical publications or report

Nice to have:

• Experience with deep reinforcement learning for LLMs, including techniques such as reward modeling, DPO, PPO etc
• Familiarity with important ideas in LLM space, such as RoPE, ZeRO/FSDP, Flash Attention, quantization
• Bachelor’s degree in Computer Science, Artificial Intelligence, Data Science, or a related field Master’s or PhD preferred
• Track record of building and delivering products (not necessarily ML-related) in a dynamic startup-like environment
• Experience in engineering complex systems, such as large distributed data processing systems or high-load web services
• Open-source projects that showcase your engineering prowess
• Excellent command of the English language, alongside superior writing, articulation, and communication skills
• Proficiency in contemporary software engineering approaches, including CI/CD, version control and unit testing

Token Factory is a part of  Nebius Cloud, one of the world’s largest GPU clouds, running tens of thousands of GPUs. We are building an inference platform that makes every kind of foundation model — text, vision, audio, and emerging multimodal architectures — fast, reliable, and effortless to deploy at massive scale. To deliver on that promise, we need an engineer who can make the platform behave flawlessly under extreme load and recover gracefully when the unexpected happens.

In this role you will own the reliability, performance, and observability of the entire inference stack. Your day starts with designing and refining telemetry pipelines — metrics, logs, and traces that turn hundreds of terabytes of signal into clear, actionable insight. From there you might tune Kubernetes autoscalers to squeeze more efficiency out of GPUs, craft Terraform modules that bake resilience into every new cluster, or harden our request-routing and retry logic so even transient failures go unnoticed by users. When incidents do arise, you’ll rely on the automation and runbooks you helped create to detect, isolate, and remediate problems in minutes, then drive the post-mortem culture that prevents recurrence. All of this effort points toward a single goal: scaling the platform smoothly while hitting aggressive cost and reliability targets.

Success in the role calls for deep fluency with Kubernetes, Prometheus, Grafana, Terraform, and the craft of infrastructure-as-code. You script comfortably in Python or Bash, understand the nuances of alert design and SLOs for high-throughput APIs, and have spent enough time in production to know how distributed back-ends fail in the real world. Experience shepherding GPU-heavy workloads — whether with vLLM, Triton, Ray, or another accelerator stack — will serve you well, as will a background in MLOps or model-hosting platforms. Above all, you care about building self-healing systems, thrive on debugging performance from kernel to application layer, and enjoy collaborating with software engineers to turn reliability into a feature users never have to think about.

If the idea of safeguarding the infrastructure that powers tomorrow’s multimodal AI energizes you, we’d love to hear your story.

• Ensure reliability, availability and performance of compute nodes running VMs
• Analyze and debug Linux systems across user space and kernel space, understanding capabilities, limitations and trade-offs at each layer
• Troubleshoot complex production issues involving CPU, memory, NUMA, cgroups and scheduling
• Work hands-on with virtualization and containerization, primarily using QEMU/KVM and Linux-native technologies
• Design and evolve observability as a core capability of the node layer: metrics, logs, traces, alerts, SLIs and SLOs
• Lead incident response, root-cause analysis, and postmortems, driving long-term reliability improvements
• Collaborate closely with platform, kernel/hypervisor, GPU and infrastructure teams to improve system design and operability

• Experience with Kubernetes internals or node-level components
• Hands-on experience with low-level Linux debugging tools (e.g. perf, eBPF, ftrace, strace, kernel crash dumps)
• Familiarity with large-scale compute or bare-metal platforms
• Contributions to open-source infrastructure or system software
• Experience debugging hardware and driver-level issues, including GPUs, NVLink, InfiniBand

Responsibilities:

• Design and develop mechanical components and assemblies for server and racks hardware
• Create 3D models, detailed drawings, and specifications using CAD tools
• Collaborate with electrical, systems, and manufacturing engineers for product integration (placement of PCBs, power supplies, cooling systems) 
• Perform thermal and structural analysis to ensure system performance and reliability (if required) 
• Support prototyping, testing, and validation of designs 
• Work with suppliers and manufacturing partners to ensure design for manufacturability (DFM) and cost efficiency 
• Identify and resolve design issues throughout the product lifecycle 

Requirements:

• Bachelor’s or Master’s degree in Mechanical Engineering or related field 
• 3+ years of experience in mechanical design, preferably in electronics or server hardware 
• Proficiency with CAD software (e.g., SolidWorks, Creo, or similar) 
• Strong understanding of thermal management, materials, and manufacturing processes 
• Experience with sheet metal design, plastics, and/or machining 
• Knowledge of data center or server systems is a plus 
• Strong problem-solving skills and attention to details 
• Ability to work effectively in a cross-functional team environment

Nice to have:

• Direct experience designing server, storage, or networking hardware 
• Expertise in thermal design, including airflow optimization, heat sink design, and liquid cooling systems
• Familiarity with data center standards and ecosystems (e.g., rack layouts, cable management, serviceability requirements)
• Experience with simulation tools (CFD/FEA) 
• Familiarity with materials selection for performance, cost, and sustainability considerations 
• Experience with rapid prototyping techniques (3D printing, CNC, sheet metal fabrication)

The role 

We are building our L3 Support Line from scratch to serve as the datacenter center of expertise for servers, firmware (BIOS/BMC), and deep Linux diagnostics across Europe and the US.

This is a senior technical role focused on deep investigations, cross-site pattern detection, and driving permanent fixes with R&D and ODM vendors. You will turn complex incidents into scalable solutions and elevate L1/L2 capabilities through strong technical enablement.

You’re welcome to work in our office in Amsterdam, the Netherlands.

Your responsibilities will include: 

Deep Technical Investigation (Primary Focus)

• Lead root cause analysis beyond L2 depth (GPU failures, firmware issues, Linux-level faults, HW/SW interactions).

• Detect recurring patterns across sites and convert findings into durable fixes.

• Own technical workstreams during high-severity incidents.

Vendor & R&D Collaboration

• Build evidence packs and drive escalations with ODM and R&D.

• Push for firmware, component, and platform-level resolutions.

• Track outcomes and ensure knowledge flows back to operations.

Firmware & Platform Readiness (BIOS/BMC)

• Support validation and rollout of firmware updates (risk assessment, staging, rollback planning).

• Help operationalize platform standards across datacenters.

Knowledge & Enablement

• Create scalable runbooks, troubleshooting guides, and error catalogs.

• Turn investigations into playbooks that elevate L1/L2 teams.

Hands-on Support (As Needed)

• Travel to datacenters for complex troubleshooting, new platform readiness, or incident containment.

We expect you to have: 

• Strong hands-on experience with datacenter servers and deep Linux troubleshooting.

• Ability to diagnose across hardware, BIOS/BMC firmware, and Linux (logs, drivers, storage basics, performance triage).

• Structured incident response experience and clear communication under pressure.

• Experience driving evidence-based escalations with vendors/R&D.

• Fluent English (written and spoken).

It will be an added bonus if you have: 

• Strong familiarity with GPU server platforms and tooling (for example: nvidia-smi, dcgmi, Linux logs correlation).

• Experience with ipmitool and Redfish workflows, firmware lifecycle, and staged rollouts.

• Scripting skills (bash and basic Python) for log collection, triage automation, and simple reliability analysis.

• Exposure to OCP-based platforms and ODM manufacturing ecosystems.

• Experience supporting enterprise bare metal customers under contractual SLAs.

The role

We are seeking a customer-obsessed Solutions Architect to lead technical engagement with Nebius customers across Europe. This role is focused on presales excellence, strong technical storytelling, and driving adoption of Nebius AI Cloud across a wide range of industry segments.

As a Solutions Architect, you will act as a trusted technical partner to customers, helping them understand, evaluate, and adopt Nebius for their AI/ML and high-performance computing workloads. You will combine deep technical expertise with strong communication skills to clearly articulate Nebius’ value proposition and differentiate our platform in a competitive market.

You’re welcome to work remotely from Europe.

Your responsibilities will include:

• Own end-to-end technical presales engagements, from discovery through solution design, PoC execution, and production readiness
• Serve as a trusted technical advisor to customer stakeholders, including CTOs, Heads of AI/ML, and platform engineering teams
• Deliver compelling technical presentations, demos, and workshops that clearly communicate the value of Nebius across different customer segments
• Execute demos and PoCs to demonstrate performance, scalability, and cost efficiency of Nebius solutions
• Translate customer requirements into scalable, production-ready architectures and best practices
• Collaborate closely with Sales, Product, and Engineering to align customer needs with Nebius capabilities and roadmap
• Act as a technical advocate for customers internally, ensuring feedback is incorporated into product and go-to-market strategy
• Support regional go-to-market efforts, including events, meetups, webinars, and technical content creation
• Contribute to building repeatable technical playbooks and assets for the European market

We expect you to have:

• 2–5+ years of experience in technical roles such as Solutions Architect, Cloud Architect, Sales Engineer, or similar, with strong customer-facing exposure
• Proven experience in presales or customer-facing technical roles, including discovery, solution design, and PoC execution
• Strong ability to deliver technical pitches and clearly explain complex infrastructure and AI/ML concepts to both technical and business audiences
• Experience positioning cloud or infrastructure solutions and articulating value propositions in competitive environments
• Solid understanding of ML/AI workloads, including training and inference, and the underlying infrastructure requirements
• Experience with cloud platforms, Kubernetes, and distributed systems
• Hands-on experience with Infrastructure as Code (e.g., Terraform) and scripting/programming (Python preferred)
• Strong communication and storytelling skills, with the ability to adapt messaging across different customer segments
• Deep understanding of the European market, including customer expectations, buying behaviors, and local ecosystem
• Fluency in English plus another language preferred (both written and spoken), with the ability to engage confidently with local customers and stakeholders
• A highly customer-centric mindset, with the ability to balance technical depth and business value

It will be an added bonus if you have:

• Experience with GPU-accelerated workloads and AI infrastructure (NVIDIA ecosystem, CUDA, etc.)
• Hands-on experience with MLOps tools and frameworks (Kubeflow, MLflow, etc.)
• Familiarity with HPC environments and schedulers (e.g., Slurm)
• Experience contributing to regional go-to-market or developer/community initiatives

The role

This role is for Nebius AI R&D, a team focused on applied research and the development of AI-heavy products. Examples of applied research that we have recently published include:

• investigating how test-time guided search can be used to build more powerful agents;
• dramatically scaling task data collection to power reinforcement learning for SWE agents;
• maximizing efficiency of LLM training on agentic trajectories.

One example of an AI product that we are deeply involved in is Nebius Token Factory — an inference and fine-tuning platform for AI models.

This role will require expertise in distributed systems to build large-scale LLM training platform.

Your responsibilities will include: 

• Designing and developing LLM training platform.
• Maintaining our ML infrastructure, ensuring optimal performance, scalability and reliability.
• Improving job scheduling strategies to minimize resource fragmentation. 

We expect you to have:

• 5+ years of professional software development experience.
• Strong software engineering skills (we mostly use Python and Go).
• Proficiency in contemporary software engineering approaches, including CI/CD, version control and unit testing.
• Experience with developing web services.
• A commitment to maintaining extreme rigor in all job-related activities.

Nice to have:

• Previous experience working with language models or other similar NLP technologies.
• A track record of building and delivering products (not necessarily ML-related) in a dynamic startup-like environment.
• Strong engineering skills, including experience in developing large distributed systems or high-load web services.
• Open-source projects that showcase your engineering prowess.

The role

We’re looking for a Software Engineer with strong C++ expertise to join the team building and operating Nebius Data Platform — a distributed storage and a processing platform that acts as the company’s “source of truth” and the backbone of many internal (and some external) products.

Nebius Data Platform is a single multi-tenant ecosystem based on YTsaurus — instead of running separate HDFS/Kafka/HBase-style systems, we provide storage, compute, and analytics capabilities inside one platform.

Built on top of the open-source YTsaurus ecosystem, we run and extend our own Nebius distribution and develop significant in-house functionality (core and platform-level). We can design, implement, and roll out features end-to-end on our clusters without waiting for upstream approvals and contribute upstream when it makes sense.

At scale today, this includes~500 servers, ~20k CPU cores and ~10 PB of compressed data in our largest production cluster, supporting workloads ranging from business-critical pipelines and financial transactions to large-scale ML/LLM training datasets and compute.

What’s inside the platform

You’ll work on a system that includes (and ties together):

• Distributed Storage (Cypress): transactional semantics, tiered storage, erasure coding, replication, and strong reliability expectations.
• Compute & ETL: a cluster-wide job scheduler (tens of thousands of cores), MapReduce, YQL for SQL-like data processing, and SPYT (Spark over YTsaurus) for modern data engineering.
• Interactive analytics (CHYT): ClickHouse® instances spun up directly on compute nodes for fast SQL over data in-place.
• Dynamic Tables: low-latency NoSQL KV with distributed ACID transactions for OLTP-style workloads and feature stores.
• Orchestracto: workflow orchestration deeply integrated with the platform (Airflow-like, but platform-native).

What you’ll do

We’re looking for engineers who combine strong systems skills with product sense: understanding who uses the platform, why certain capabilities matter, and making pragmatic trade-offs to maximize impact. On our team, engineering work is expected to be connected to real users and outcomes — you’ll regularly align with internal stakeholders, clarify requirements, and help drive prioritization.

In this role, you will:

• Design and implement new functionality in YTsaurus core (C++) with production reliability in mind.
• Build and evolve platform-level capabilities: platform architecture and operating model—multi-cluster growth, shared primitives, and a consistent experience that scales with new teams and use cases.
• Improve end-to-end platform experience for internal (and external-facing) users: APIs, guardrails, debugging workflows, and automation.
• Own production quality: incident response / on-call rotation, root cause analysis, and turning learnings into durable fixes.

Example projects

• Roll out sharded YTsaurus masters (incl. Kubernetes operator support) and build automatic balancing of metadata across master cells (consensus groups) to remove control-plane bottlenecks and unlock 10–100x cluster growth.
• Make CHYT interactive SQL faster and more predictable at high load via performance work like data-skipping / min-max-style indexes and improved execution introspection.
• Turn Orchestracto into a platform product by defining the building blocks, developer experience, and governance for how teams create and share workflows.
• Scale and harden Parquet-on-S3 for native YTsaurus workloads by tackling replication/movement, consistent lifecycle semantics, and master-server metadata optimizations for performance and reliability.
• Design and ship complete, trustworthy audit trails for data changes (who/what/when) across heterogeneous storage and compute paths.

Tech stack

• Core: modern C++ (C++20, async + multithreaded primitives)
• Services & tooling: Go and Python (microservices, utilities, integration tests)

What we expect

• 5+ years of software engineering experience.
• Strong C++ skills (you’ll write core code).
• Working knowledge of Python and/or Go (you don’t have to be expert, but should be comfortable navigating them).
• Experience developing and/or operating high-load, distributed services.
• Production mindset: ability to use SSH, read logs/metrics/traces, and debug distributed systems behavior.
• Solid CS fundamentals: algorithms, data structures, concurrency basics.

Nice to have

• Experience with Big Data systems (YTsaurus/Hadoop/Spark/ClickHouse/Kafka-like ecosystems).
• Experience with multi-tenant platforms, schedulers, resource isolation, quotas, and reliability engineering.
• Strong performance engineering skills (profiling, lock contention, latency/throughput tradeoffs).

We conduct coding interviews as part of the process.

The role

We’re looking for a Senior Backend Engineer to join our Storage Virtualization Team, building a distributed, fault-tolerant storage system for Nebius’ hyperscaler cloud.
You’ll work on high-performance block and filesystem storage that delivers sub-millisecond latency, millions of IOPS and terabytes per second of throughput, even in the face of hardware failures.

• Virtualization: virtio-blk and virtio-fs, QEMU and vhost-user, performance-critical I/O paths
• Networking: high-throughput VM-to-storage transport over TCP and RoCEv2 (RDMA)
• Storage systems: replication, consensus, self-healing, and data migration

• 6+ years of professional software engineering experience
• Strong knowledge of C++
• Solid understanding of algorithms and data structures
• Basic knowledge of operating system internals (I/O, memory, scheduling)
• Ability to write reliable, maintainable code and debug complex systems
• Team-oriented mindset and fluency in English

We conduct coding interviews as part of the process.

The role

Our CloudGate team is responsible for the software side of external network connectivity in our Cloud. We're building a traffic delivery system for a variety of scenarios: IPv4 connectivity, Cloud Interconnect, Egress NAT, and a network load balancer. They serve tens of millions of packets per second.

We have a control plane microservice architecture with gRPC transport and our own Database as our data warehouse.

What we do:

• Increase service scalability
• Developing service functionality with support for service endpoints and expansion of health check types
• Improve the internal architecture, optimizing interaction with related services 

In this position, your responsibility will be to:

• Developing a data plane for Nebius Cloud network services
• Improve service performance and reliability
• Automate complex cross-service interaction scenarios
• Perform load testing for services

We expect you to have:

• Capable of writing reliable, high-performance code
• Proficient in C and ready to learn Go/C++
• Familiar with routing network traffic

It would be an added bonus if you had:

• Worked with VPP, DPDK, and the Linux kernel network subsystem
• Well-versed in virtual networks and overlays, SDN, NFV, DPI, network protocols, routing and tunneling, BGP, and MPL

We conduct coding interviews as part of the process.

The role

Nebius is looking for a Product Manager. You’re welcome to work in our offices in Amsterdam or Belgrade.

Your responsibilities will include: 

• Develop… 

• Collaborate with… 

• Manage…  

We expect you to have: 

• Experience as… (job title — e.g. a software engineer) 

• Experience in… (a domain, industry — e.g. in sales, marketing, or a similar role) 

• Experience… (doing something  — e.g. exploiting vulnerabilities in web applications 

• Experience with… (techniques, approaches — e.g. threat-modeling techniques) 

• Familiarity with… 

• Understanding of…  

• Knowledge of… 

• Background in… 

• Demonstrated ability to… (do something — e.g. work independently) 

• Working knowledge of spoken and written English 

It will be an added bonus if you have: 

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!

We are looking for an Automations Engineer to design and build scalable automation solutions across modern IT and SaaS environments. This role is ideal for someone who enjoys working with APIs, cloud services, and workflow automation to drive efficiency and reduce manual processes.

Key Responsibilities

• Design, build, and maintain automation workflows across IT systems and SaaS platforms
• Develop integrations between Microsoft 365, Microsoft Entra ID, Google Workspace, and other tools using APIs
• Automate operational processes such as user lifecycle management, notifications, data synchronization, and access workflows
• Implement secure and reliable automations with logging, monitoring, and error handling
• Continuously optimize processes to reduce manual effort and improve efficiency
• Collaborate with IT, Security, and business teams to deliver automation solutions
• Create and maintain clear documentation for workflows, scripts, and integrations

Requirements

• 3+ years of hands-on experience in automation, scripting, or IT infrastructure in enterprise environments
• Strong experience with:
  • Microsoft Entra ID & Microsoft 365 ecosystem
  • Google Workspace (basic administration)
• Hands-on experience with:
  • RESTful APIs and system integrations
  • PowerShell and/or Python
  • Azure services (Automation, Functions, Logic Apps)
• Solid understanding of:
  • Automation patterns (event-driven, scheduled workflows)
  • SaaS integrations and API-based workflows
  • Authentication protocols (OAuth, OpenID Connect)
• Familiarity with tools such as Slack, Jira, Git, and basic CI/CD pipelines
• Strong troubleshooting and problem-solving skills
• Intermediate English (written and spoken)

Nice to Have

• Experience with:
  • Slack API / Atlassian tools (Jira, Confluence)
  • Microsoft Graph API
  • Google Admin SDK
• Knowledge of Azure Monitor / Log Analytics
• Experience working in large-scale or multi-system environments

Why Join?

• Work on modern cloud and SaaS ecosystems
• Drive real impact through automation and efficiency gains
• Collaborate in a cross-functional, technology-driven environment
• Opportunity to grow your expertise in cloud, APIs, and automation architecture

• Build prototypes and demos across the product portfolio — serverless inference, databases, MLflow, MLOps, and vertical use cases in Physical AI and HCLS — that become assets for sales, product, and engineering teams
• Support new customers hands-on through POC design, technical onboarding, and validation; act as the bridge between their ML team and the platform during the critical first months
• Go deep on emerging applied AI — new training techniques, inference optimizations, agentic architectures, new frameworks — and turn findings into working prototypes, writeups, and product recommendations
• Feed the product roadmap with specific, grounded feedback; be the voice of "here's what broke in three customer POCs last month and here's what needs to change"
• Develop reusable technical assets — notebooks, reference architectures, benchmark results — that reduce onboarding friction at scale

• You've fine-tuned large models, debugged distributed training jobs, built production RAG or agentic pipelines, and optimized inference on GPU infrastructure — not just read about it
• You're fluent in the modern ML stack: PyTorch, HuggingFace, CUDA fundamentals, Kubernetes for ML, MLflow or equivalent, vector databases
• You've worked with enterprise ML teams — whether as a solutions engineer, customer engineer, or an ML engineer who collaborated closely with customers
• You read papers and implement them — not for credit, but because it's how you stay sharp
• You communicate with calibration: you can explain activation checkpointing tradeoffs to an ML engineer in the morning and the cost implication to a CTO in the afternoon

• Experience in any of our vertical domains: Physical AI / robotics / simulation, HCLS (drug discovery, medical imaging, clinical NLP), or enterprise AI application development
• Familiarity with MLOps at scale (Kubeflow, Metaflow, Argo, Ray)
• Prior work at a cloud provider or AI infrastructure company
• You've shared technical work publicly — notebooks, talks, blog posts that people actually use

• Competitive salary and comprehensive benefits package.
• Opportunities for professional growth within Nebius.
• Flexible working arrangements.
• A dynamic and collaborative work environment that values initiative and innovation.

• Optimize I/O for emulated disk and network devices
• Integrate the hypervisor with other platform services and storage facilities for user data
• Efficiently distribute resources between virtual machines
• Improve guest system support
• Advance the cutting-edge of open source virtualization
• Provide low-level security for the hypervisor and emulator
• Provide general support, fix bugs, and monitor the upstream
• Collaborate with other team members and stakeholders

• 5+ years of professional software engineering experience
• Fluent in C programming language
• 3+years of experience with Linux
• At least 3 years of engineering experience with QEMU/KVM
• General understanding of x86-compatible systems (virtual memory, interrupts, privilege rings)
• Experience writing general system code in user mode for Linux, including debugging, analysis, and optimization tools (the emulator is built on the user mode system process for Linux)

• Aсcepted patches in Linux Kernel or QEMU/KVM
• Experience working with Linux kernel
• Some experience with ARMv8, including virtualization extensions
• Understanding of PCI, SCSI, and ACPI
• Experience working with the Linux kernel
• Excellent communication skills for cross-team collaboration
• Strong work ethic

We conduct coding interviews as part of the process.

The role

Your responsibilities will include:

• Participate in the design, deployment, and maintenance of high-performance cloud systems tailored for AI workloads.
• Arranging and performing hardware R&D tests and experiments on site in data center
• Troubleshoot and resolve complex system issues related to GPUs, networking (InfiniBand, NVLink), PCIe, and server infrastructure.
• Conduct deep investigations into hardware, software, and networking problems to ensure optimal system performance and reliability.
• Participate in development of tests and test methodologies for advanced GPU, InfiniBand, and Compute systems to benchmark and validate performance.
• Collaborate with cross-functional teams to improve system performance and reliability.
• Monitor system performance and continuously fine-tune configurations for maximum efficiency

Required Skills & Qualifications: 

• Strong knowledge of modern server architecture, especially in high-performance GPU-based environments.
• Hands-on experience with GPUs, Network, NVLink, and PCIe.
• Proficient in Linux systems, with expertise in Python and Bash scripting for automation.
• Demonstrated ability to troubleshoot complex system issues, including hardware, software, and networking problems.
• Experience with deep problem investigation, root cause analysis, and resolving performance issues in cloud-based or high-performance computing environments.
• Strong analytical and problem-solving skills, with a focus on optimizing system performance.
• Basic electronics modification by soldering and wiring

It will be an added bonus if you have:

• Knowledge of the Linux kernel and experience with kernel-level troubleshooting.
• Familiarity with electronic measurement equipment: oscilloscope, multimeter. 

The role 

Nebius is looking for candidates to strengthen its datacenter facilities engineering team. You will work, individually and in collaboration, with internal business partners (Technical Project managers, Data Center IT, IT Procurement, Network Engineering) and with external vendors to validate and test installation & operation performance of data center mechanical systems. 

This role requires a flexible, pro-active mindset with attention for details and good communication skills, and a willingness to travel.

You’re welcome to work in our office in Amsterdam, hybrid or remotely.

Your responsibilities will include: 

• Plan and implement cost-effective and reliant mechanical designs and distribution systems
• Work with internal business partners like Technical Project Management, Data Center IT, IT Procurement, Network Engineering, and with external vendors to validate and test installation & operation performance of data center mechanical systems
• Create designs which meet and exceed Nebius’s quality benchmarks within our budget capacity
• Seek new designs and amalgamate new technologies within Nebius AI’s data center planning and infrastructure
• Identify and document list of electrical equipment and components required during the build/installation phase
• Work on multiple projects in different locations, and visit the construction sites to oversee the work of external vendors and contractors

We expect you to have: 

• Minimum Bachelor’s degree in building services engineering or mechanical engineering, or 10+ years of relevant mechanical engineering experience in mission critical facilities environment including but not limited to: data centers, power generation and oil/gas facilities
• 7+ years of experience in creating mechanical design documentation for construction
• 7+ years of experience in commercial and/or Industrial Mechanical design
• In-depth knowledge of data centre design, BMS & HVAC design and related product development
• In-depth knowledge and understanding of data centre mechanical systems, chillers air-cooled & water-cooled, pumps, cooling towers, heat exchangers, CRAHs/CRAC, fans, air economizers, water treatment etc.
• Good understanding of electrical equipment and system designs related to data centers
• Good data analysis skills
• Excellent communication skills, attention to detail and ability to maintain high quality standards

It will be an added bonus if you have: 

Required qualification + one or two certifications like:

• CDCE (Certified Data Centre Expert or Equivalent Highest Certification)
• CDCS (Certified Data Centre Specialist or Equivalent Intermediate Certification)
• CDCP (Certified Data Centre Professional or Equivalent Basic Certification)
• CDCDP (Certified Data Centre Design Professional or Equivalent)
• DCIE (Data Centre Infrastructure Expert or Equivalent)

The role

Nebius seeks a Key Customers Solutions Architect to support key and strategic Nebius GPU Cloud services customers. In this role, you will be a trusted technical advisor, helping clients design, deploy, and scale AI solutions while managing large-scale GPU workloads involving hundreds to thousands of GPUs. You will also collaborate with sales and product teams to drive growth and enhance customer satisfaction.

You’re welcome to work remotely from Europe.

Your responsibilities will include: 

• Serve as the primary technical point of contact, troubleshooting and resolving complex AI/ML.
• Guide customers in optimizing GPU performance for ML training and inference workloads, ensuring seamless integration and scalability.
• Partner with the sales team to identify new opportunities, promote the latest products, and deliver technical presentations.
• Act as a bridge to product teams, providing customer feedback, relaying feature requests, and ensuring alignment with customer requirements.
• Engage with internal and external stakeholders, negotiate solutions, and effectively drive alignment to address customer challenges.

We expect you to have:

• Experience: 5 - 10 + years in roles like Cloud Solutions Architect, Technical Account Manager, or Customer Engineer, with hands-on experience in cloud services and AI/ML workloads.
• Proficiency in Infrastructure as Code (IaC) tools like Terraform and Ansible.
• Experience with Kubernetes and Python programming.
• Solid understanding of GPU computing, including ML training, inference workloads, and GPU stacks (e.g., CUDA, OpenCL).
• Customer-centric approach with a proven ability to build trust and foster long-term relationships.
• Strong ability to explain technical concepts to technical and non-technical audiences.

It will be an added bonus if you have:

• Hands-on experience with HPC/ML orchestration frameworks (e.g., Slurm, Kubeflow).
• Experience with deep learning frameworks (e.g., PyTorch, TensorFlow).
• Familiarity with ML tools from NVIDIA, AWS, Azure, and Google Cloud providers.
• Strong project management skills, with the ability to prioritize tasks and deliver on deadlines.
• Proven experience mentoring technical teams and driving team growth.
• Expertise in stakeholder negotiation to support problem resolution and ensure seamless collaboration.

The role 

We are seeking a highly skilled Systems Engineer (Cloudmeter) to join our team to support benchmarking of GPU platforms for machine learning and AI workloads. You will play a critical role in evaluating the performance of GPU-based hardware for various deep learning and AI frameworks, enabling data-driven decisions for platform optimization and next-generation hardware development.

In this position, your responsibility will be to:

• Work closely with hardware, development teams to profile and analyze GPU performance at the system and kernel level.
• Evaluate and compare GPU performance across different platforms, architectures, and software stacks (e.g., CUDA, ROCm).
• Perform acceptance testing for new GPU clusters, ensuring hardware and software meet performance, stability, and compatibility requirements for AI workloads.
• Perform experiments across diverse GPU system configurations to assess the impact of varying interconnect strategies and system-level optimizations on performance and scalability.

We expect you to have:

• Proficient in Unix/Linux, plus Python and Bash for automation.
• Good understanding of the GPU stack: CUDA,NCCL, drivers, and relevant libraries
• Proven ability to troubleshoot complex system issues including hardware, software, and networking problems.
• Familiarity with containerized environments (e.g., Docker, Kubernetes).

Ways to stand out from the crowd:

• Experience with modern deep learning frameworks (PyTorch, JAX, vLLM, Tensort-LLM)
• Experience with job schedulers and resource managers (Slurm, Volcano, etc.).

The role 

Nebius is looking for candidates to strengthen its datacenter facilities engineering team. You will work,
individually and in collaboration, with internal business partners (technical teams, especially technical
project managers and different vendors), to deliver planning and design, and to oversee the
construction and implementation of the electrical engineering aspects of our data centers.

This role requires a flexible, pro-active mindset with attention for details and good communication
skills, and a willingness to travel.

You’re welcome to work in our office in Amsterdam, hybrid or remotely.

Your responsibilities will include: 

• Plan, validate and verify the roll out of reliant electrical systems
• Work with our internal and external business partners
• Create designs which meet and exceed Nebius’s quality benchmarks on time and within budget
• Seek new designs and amalgamate new technologies within Nebius AI’s data center planning and infrastructure  

We expect you to have: 

• Bachelor’s degree in electrical engineering, or equivalent experience
• 5+ years of experience in creating electrical design documentation for construction
• 5+ years of experience in commercial and/or industrial electrical design
• In-depth understanding of electrical equipment such as: power distribution, busway systems, electrical switchgear, UPS, and diesel generators
• Basic understanding of mechanical equipment and systems related to data centers
• Good communication skills, fluent in English
• A flexible, pro-active mindset with attention for details

It will be an added bonus if you have: 

• Experience with designing, operating, or maintaining mission critical facilities
• Experience with the application of regional and international standards
• CDCDP, Uptime, or other similar certificates
• Knowledge of and experience with the roll-out of DC (direct current) power distribution systems

The team

Customer experience at Nebius GPU AI Cloud involves tackling customers’ challenges and directly impacting their success by solving real-world AI and ML problems at massive GPU cloud scale. You’ll not only resolve issues, but play a key role in shaping clients’ business success by optimizing their AI solutions. Working with advanced GPUs such as H200, B200 and GB200, as well as modern ML frameworks, you’ll influence the development of the Nebius AI Cloud and gain experience at the intersection of infrastructure and AI. With minimal bureaucracy, you’ll have the freedom to innovate, take ownership and drive change. Opportunities for growth are abundant in this vibrant and supportive professional community.

The role

We are seeking a highly skilled and customer-focused leader to join our team as a Cloud Solutions Architect Lead. As a team leader, you will play a pivotal role in customer success across EU region, both managing the efforts of Cloud Solutions Architects team (technical and process excellence, talent development) and building processes alongside your stakeholders. Player-coach mentality and proven track record of managing high expertise teams is a must. 

You’re welcome to work from our office in Amsterdam or remotely from any EU country.

Your responsibilities will include: 

• Lead and mentor a team of Solutions Architects, fostering a culture of technical excellence, customer empathy, and collaborative execution.
• Oversee and participate in technical engagements including PoCs, workshops, architecture reviews, and trainings.
• Drive consistency and quality across infrastructure design, IaC practices, technical documentation, and customer enablement content.
• Collaborate closely with Product and Development teams, representing customer needs and helping shape the roadmap.
• Guide customers in optimizing ML/AI/HPC pipelines for performance, scalability, and cost-efficiency on Nebius  cloud infrastructure.
• Build visibility and ownership culture amongst Solutions Architects.

We expect you to have: 

• 5+ years of experience in a technical role (Solutions Architect, DevOps Engineer, ML Engineer, or similar) with a focus on cloud-native systems and distributed computing.
• 2+ years of experience leading or mentoring customer facing engineering teams.
• Deep hands-on experience with Infrastructure as Code (Terraform, Ansible), Kubernetes, and cloud automation.
• Strong communication and stakeholder management skills across both technical and non-technical audiences.
• Passion for developing scalable, reliable cloud architectures and driving customer success.

It will be an added bonus if you have: 

• Experience with HPC or ML orchestration frameworks (e.g., Slurm, Kubeflow, Ray).
• Strong coding skills in Python and experience with GPU computing environments for ML/AI workloads.
• Proficient in GPU stack components (e.g., CUDA, cuDNN) and cloud-native patterns for ML training/inference.
• Familiarity with deep learning frameworks (e.g., TensorFlow, PyTorch, JAX).
• Understanding of cloud-based ML tools and offerings from NVIDIA, AWS, Azure, or Google Cloud.
• Experience participating in or leading technical contributions to conferences or open-source communities. 

The role 

The Data Engineering team is responsible for building and maintaining robust data infrastructure that powers analytics, and business intelligence across Nebius. We design and implement scalable data pipelines, optimize data storage and processing, and enable data-driven decision making across the organization. The team works closely with product teams and business stakeholders to ensure alignment with company goals.We are looking for a Data Engineer to design, build, and maintain our data infrastructure and pipelines. You will work on processing large-scale datasets, optimizing data workflows, and enabling analytics capabilities that support our rapidly growing cloud platform.

Your responsibilities: 

• Design, develop, and maintain scalable data pipelines.
• Build and optimize data infrastructure.
• Implement data quality monitoring and validation frameworks.
• Optimize data storage, processing, and query performance for large-scale datasets.
• Design and implement data models for analytics and reporting use cases.
• Develop tools and automation to improve data engineering workflows and productivity.
• Ensure data governance, security, and compliance standards are met.
• Participate in on-call rotation to support production data systems.

Must-haves: 

• 3+ years of experience in data engineering or related roles.
• Experience building and maintaining data pipelines using orchestration tools (e.g., Airflow, Prefect, Dagster).
• Strong proficiency in SQL and solid programming skills in Python.
• Experience with distributed data processing frameworks (e.g., Apache Spark, or similar).
• Knowledge of data modeling principles and best practices.
• Understanding of data architectures and storage systems.

Nice-to-haves: 

• Experience with real-time data streaming platforms.
• Familiarity with Infrastructure as Code tools (Terraform, etc).
• Experience with containerization (Docker) and Kubernetes.
• Knowledge of data governance and privacy frameworks (GDPR, SOC2).
• Knowledge of data quality and observability tools (Great Expectations, etc.).

We conduct coding interviews as part of the process.

The role

We are looking for a Customer Engineer to support key and strategic Nebius GPU Cloud services customers. In this role, you will be a trusted technical advisor, helping clients design, deploy, and scale AI solutions while managing large-scale GPU workloads involving hundreds to thousands of GPUs. You will also collaborate with sales and product teams to drive growth and enhance customer satisfaction.

You’re welcome to work remotely from Europe.

Your responsibilities will include:

• Serve as the primary technical point of contact for troubleshooting and resolving complex AI/ML issues.
• Guide customers in optimizing GPU performance for ML training and inference workloads, ensuring seamless integration and scalability.
• Partner with the sales team to identify new opportunities, promote the latest products, and deliver technical presentations.
• Act as a bridge to product teams, providing customer feedback, relaying feature requests, and ensuring alignment with customer requirements.
• Engage with internal and external stakeholders, negotiate solutions, and effectively drive alignment to address customer challenges.

We expect you to have:

• Experience: 5+ years in roles like Solutions Architect, Technical Account Manager, or Customer Engineer, with hands-on experience in cloud services and AI/ML workloads.
• Proficiency in Infrastructure as Code (IaC) tools like Terraform and Ansible.
• Experience with Kubernetes and Python programming.
• Solid understanding of GPU computing, including ML training, inference workloads, and GPU stacks (e.g., CUDA, OpenCL).
• Customer-centric approach with a proven ability to build trust and foster long-term relationships.
• Strong ability to explain technical concepts to technical and non-technical audiences.

It will be an added bonus if you have:

• Hands-on experience with HPC/ML orchestration frameworks (e.g., Slurm, Kubeflow).
• Experience with deep learning frameworks (e.g., PyTorch, TensorFlow).
• Familiarity with ML tools from NVIDIA, AWS, Azure, and Google Cloud providers.
• Strong project management skills, with the ability to prioritize tasks and deliver on deadlines.
• Proven experience mentoring technical teams and driving team growth.
• Expertise in stakeholder negotiation to support problem resolution and ensure seamless collaboration.

Why work at Nebius
Nebius is leading a new era in cloud computing to serve the global AI economy. We create the tools and resources our customers need to solve real-world challenges and transform industries, without massive infrastructure costs or the need to build large in-house AI/ML teams. Our employees work at the cutting edge of AI cloud infrastructure alongside some of the most experienced and innovative leaders and engineers in the field.

Where we work
Headquartered in Amsterdam and listed on Nasdaq, Nebius has a global footprint with R&D hubs across Europe, North America, and Israel. The team of over 1400 employees includes more than 400 highly skilled engineers with deep expertise across hardware and software engineering, as well as an in-house AI R&D team.

Summary:

Location: Amsterdam
Duration: 3 months
Start date: June 2026 
Compensation: Paid
Eligibility: Current University student (Computer Science or related field), Recent Graduate or Early Career specialist
Work authorization: Permitted to work in the job’s location

The role

We are looking for an Early Talent to develop cloud-based integrations on Microsoft Azure. You will work with experienced engineers and gain hands-on experience building API-based and cloud-native integration solutions.

We expect you to have

• 0–2 years of experience with Microsoft Azure (study projects, internships, or junior roles count).
• Basic understanding of cloud concepts (compute, storage, networking).
• Familiarity with Infrastructure as Code (Terraform / Bicep / ARM) — even at learning or pet-project level.
• Basic experience with CI/CD concepts (e.g., GitHub Actions, Azure DevOps, or similar).
• Understanding of:
   - Azure Networking basics (VNet, NSG, public/private access)
   - Compute basics (VMs, containers)
   - Storage services
• Awareness of identity concepts (RBAC, basics of Microsoft Entra ID).
• Basic scripting skills (PowerShell / Bash / Python — even simple scripts).
• Interest in monitoring and logging (Azure Monitor, Log Analytics — basic exposure is enough).
• Understanding of cloud fundamentals, security basics, and cost awareness.
• English: Intermediate.

Your responsibilities will include

• Assist in managing Azure environments and subscriptions.
• Support infrastructure deployments using Infrastructure as Code.
• Help build and maintain CI/CD pipelines under supervision.
• Assist with configuration of networking and access controls.
• Monitor system health and report issues.
• Support cost optimization and resource cleanup.
• Follow and help enforce Azure policies and governance.
• Collaborate with engineering teams on cloud-related tasks.
• Maintain and update documentation.

What we offer

• Competitive salary and comprehensive benefits package.
• Mentorship from experienced AI, ML, and cloud infrastructure professionals.
• Hands-on experience with real customer workloads and production systems.
• Opportunities for professional growth within Nebius.
• A dynamic and collaborative work environment that values initiative and innovation.
• Opportunity to be considered for a full-time role after the Early Talent Program.

About the Role
We are looking for a QA Engineer specializing in servers and server components to ensure quality, performance, reliability, and compatibility for purpose of modern server platforms.
In this role, you will work closely with hardware, firmware, system, services, and application teams to validate server architectures and components across the full product lifecycle - from early prototypes to production deployment.

Responsibilities
System & Component Validation
• Qualify complete server system architecture, including compute, memory, storage, networking, and accelerators
• Test and validate interactions between server components: CPU, DRAM, NVMe devices, Network interface cards (NICs), GPUs / accelerators.
• Perform individual component testing to verify performance, stability, and reliability prior to and after system integration
• Execute system-level validation under different configurations, workloads, and use cases
• Evaluate benchmark results against: technical specifications, business and application requirements, historical baselines and previous generations
• Identify performance regressions, instability, and reliability issues under sustained load and stress conditions
• Ensure hardware components and firmware meet business needs, performance goals, and specifications

Firmware, BIOS & BMC Validation
• Test and validate firmware for BMC / BIOS / FPGA
• Validate BMC functionality including IPMI/Redfish, sensors, power, thermal management, and logging
• Perform firmware upgrade, downgrade, and regression testing
• Assess firmware impact on performance, stability, and reliability across different hardware configurations
• Prepare and maintain test cases, checklists, and test reports
• Participate in platform validation for manufacturing and production readiness

Required
• Strong understanding of server system architecture
• In-depth knowledge of server components and their operation:
• Experience with component-level and system-level testing
• Understanding of BIOS/UEFI and BMC fundamentals
• Practical experience with Linux (command line, system tools, logs)
• Scripting skills (e.g. Bash, Python) for test and benchmark automation
• Ability to analyze performance data and identify regressions or anomalies
• Strong debugging, documentation, and communication skills

Nice to Have
• Experience with data center or server-grade hardware platforms
• Familiarity with common bench-marking and stress tools
• Understanding of PCIe topology and system interconnects
• Experience with reliability, power, and thermal testing
• Exposure to production, manufacturing, or fleet-scale validation
• Experience working with early hardware prototypes

The role 
We are seeking an Enterprise Applications Engineer with a strong focus on the Atlassian Cloud ecosystem to join our Enterprise Technologies team. In this role, you will be primarily responsible for the administration, configuration, and continuous improvement of our Atlassian Cloud ecosystem — including Jira, Confluence, Assets, and Statuspage.
You will collaborate with cross-functional teams to ensure our business applications remain secure, efficient, and aligned with organisational needs.
This position is ideal for someone with strong hands-on experience in Atlassian administration who wants to grow their skills in SaaS management, integrations, and automation across the enterprise stack.

You’re welcome to work in our office in Amsterdam or remotely.

Your responsibilities will include: 

• Administer, configure, and maintain Atlassian Cloud applications (Jira Software, Jira Service Management, Confluence, Access, Statuspage).
• Design and manage Jira workflows, automation rules, custom fields, and permission schemes aligned to organizational standards.
• Implement and support Atlassian Access for identity federation (SSO, SCIM) with Azure Entra ID.
• Manage Confluence spaces, templates, and permissions, ensuring consistent governance and structure across departments.
• Develop and maintain automations and integrations using Atlassian APIs, webhooks, and tools like Automation for Jira, ScriptRunner, or similar.
• Partner with Security, Compliance, and IT Governance to ensure adherence to data retention, access control, and audit requirements.
• Maintain documentation, change logs, and configuration records for Atlassian environments.
• Monitor system performance, capacity, and usage metrics, ensuring uptime and proactive issue resolution.
• Collaborate with project teams and business owners to optimize use cases and deliver platform enhancements.
• Provide user support, training, and best-practice guidance for Atlassian tools.
• Support related SaaS integrations (e.g., Slack, Zoom, DocuSign etc) as needed for cross-tool workflows. 

We expect you to have: 

• 3–5 years of hands-on experience administering and supporting Atlassian Cloud (Jira Software, Jira Service Management, Confluence).
• Strong understanding of Jira project configurations, workflows, automation, permission models, and notification schemes.
• Experience with Confluence space management, page templates, and content governance.
• Familiarity with SSO, SCIM, and user lifecycle management via Azure Entra ID (Azure AD).
• Knowledge of Atlassian Marketplace apps and their configurations.
• Experience with API integrations or automation scripting (Python, PowerShell, or similar).
• Understanding of SaaS governance principles, including BCP/DRP documentation and access reviews.
• Excellent problem-solving and communication skills with a collaborative mindset.
• Passion for process improvement, automation, and knowledge sharing.  

Summary:

Location: Amsterdam
Duration: 3 months
Start date: June 2026 
Compensation: Paid
Eligibility: Current University student (Computer Science or related field), Recent Graduate or Early Career specialist
Work authorization: Permitted to work in the job’s location

Why work at Nebius
Nebius is leading a new era in cloud computing to serve the global AI economy. We create the tools and resources our customers need to solve real-world challenges and transform industries, without massive infrastructure costs or the need to build large in-house AI/ML teams. Our employees work at the cutting edge of AI cloud infrastructure alongside some of the most experienced and innovative leaders and engineers in the field.

Where we work
Headquartered in Amsterdam and listed on Nasdaq, Nebius has a global footprint with R&D hubs across Europe, North America, and Israel. The team of over 1400+ employees includes more than 400 highly skilled engineers with deep expertise across hardware and software engineering, as well as an in-house AI R&D team.

Your responsibilities will include

• Primary Focus: learning network operations while supporting the team with routine and low-risk tasks across data center and backbone networks under close supervision.
• Operational Support (Supervised):
  • Assist in day-to-day network operations for data center and backbone environments.
  • Perform simple, well-defined tasks from the backlog under guidance: configuration updates, checks, and data collection.
  • Help with hardware installation tasks (rack, cable, label) under supervision.
• Network Stability & Safe Execution:
  • Deploy pre-approved and tested configurations following clear instructions.
  • Strictly follow change management and operational procedures.
  • Escalate any unclear behavior or unexpected results immediately.
• Learning & Growth:
  • Actively study networking fundamentals: Ethernet, IP, routing, DC and backbone basics.
  • Learn internal tools, workflows, and operational standards.
  • Gradually expand task scope as skills and reliability improve.

What we offer

• Competitive salary and comprehensive benefits package.
• Mentorship from experienced AI, ML, and cloud infrastructure professionals.
• Hands-on experience with real customer workloads and production systems.
• Opportunities for professional growth within Nebius.
• A dynamic and collaborative work environment that values initiative and innovation.
• Opportunity to be considered for a full-time role after the Early Talent Program.

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!

The Role

We’re looking for a Network Site Reliability Engineer (NetSRE) to help build and run the fundamental part of Nebius - the Network - the infrastructure everything else depends on. This is an engineering-first SRE role: you’ll set clear reliability targets, build the tooling and automation to meet them, and make the network safer to operate as we scale quickly.

Your responsibilities will include:

• Define and own reliability goals for network services and critical paths (SLIs/SLOs, availability targets, error budgets where it makes sense)

• Drive reliability improvements across the whole network: not only services, but also site readiness, inter-site connectivity (DCI), and operational standards

• Own incident response for your areas, lead investigations/postmortems, and turn failures into durable fixes (not repeated firefighting)

• Build and evolve observability: actionable metrics/logs/traces, alerting, and faster debug loops during and after incidents

• Design safer change workflows: automation, CI/CD, test/staging environments, canarying, rollbacks, and auditability for network changes

• Work closely with network engineers and platform teams to embed operability into designs and keep operations practical and fast

We expect you to have:

• Strong production Linux fundamentals and a structured approach to debugging complex systems

• Solid understanding of networking basics and how real networks fail (control plane vs data plane, latency/loss, failure domains, etc.)

• Hands-on experience operating high-availability systems and improving them over time (not just “keeping lights on”)

• Ability to write and maintain software/automation (Go is common for us; Python is also welcome)

• Experience with modern infrastructure tooling (e.g., IaC, CI/CD, container platforms) and comfort automating operational workflows

It will be an added bonus if you have:

• Experience with high-throughput traffic processing: load balancers, tunneling/decap, NAT64, or similar datapath-heavy systems

• Low-level networking performance/debug background (eBPF/XDP, DPDK, perf/ftrace, kernel networking internals)

• Experience building network-safe delivery pipelines (testing labs, staged rollouts, automated verification, drift detection)

• Background with large-scale network observability/telemetry (e.g., routing/flow telemetry, regression detection at scale)

The role

We are looking for a Senior Network Engineer to join our team to ensure smooth and stable operation of data center infrastructure, points of presence, and our own backbone network. The engineer will also design and develop data center networks with thousands of server ports, InfiniBand-based GPU cluster interconnect networks, and automation and management tools for such networks.

You’re welcome to work in our office in Amsterdam.

Your responsibilities will include:

• Provide technical design, operations, duties and assistance to related cross-functional teams, including the internal R&D team, HWaaS, and all-around cloud overlay & underlay network environments.
• Develop monitoring and automation tools.
• Contribute to the launch of new regions within our cloud and GPU platforms.

We expect you to have:

• Expert-level (jncie/ccie) expertise in MPLS, routing and switching Service Provider and DataCenter networks, Ethernet switching/vxlan, routing (BGP/isis), SR mpls+v6, traffic balancing/ECMP, l3 mpls VPN, and cloud overlay network technologies.
• Experience in developing and documenting a network design.
• Experience in developing plans for testing network infrastructure and vendors.
• Experience diagnosing problems with the TCP/IPv4/v6 protocol stack in a CLOS topology data center network.
• Knowledge of the design and internal architecture of modern network equipment, QoS mechanisms, and operations.
• Experience working with Juniper, Arista, Huawei, and Mellanox switches and routers.
• Working proficiency in English.

It would be an added bonus if you had:

• Working proficiency in any other European language
• Working knowledge of public clouds and GPU+infiniband networking
• Knowledge of software-defined networking overlays for the cloud environment
• Knowledge of Python, Go, or other popular programming languages in the Linux environment.
• Experience using these programming languages for task automation.

The role

We’re looking for a Senior Backend Software Engineer to help develop our hyperscaling platform.
We have a lot of tasks on Golang and little less on Java and Python.
You’re welcome to work from our office in Prague or in Amsterdam, hybrid or remotely. 

In this position, your responsibility will be to:
Developing fault-tolerant, reliable cloud services: cloud infrastructure, managed databases, managed Kubernetes, billing, monitoring systems, ML service and more.

We expect you to have:

• 5+ years of professional software engineering experience
• Excellent knowledge of Golang or you are ready to quickly switch to this programming language
• Ability to write reliable code and dig into complex problems
• Teamwork-oriented approach

It would be an added bonus if you had:

• Experience designing high-load and scaling services

We conduct coding interviews as part of the process.

The Product

In a rapidly evolving world, trust in AI depends on AI agents being grounded in fresh, verified real-world data. Search is the foundation that makes this possible.

We are building an agent-native search platform designed specifically for AI systems rather than human users. Our product provides programmatic, low-latency, and observable search APIs that AI agents use to retrieve, filter, and reason over real-world information at scale.

The Role

We are looking for a Senior Software Engineer to work on the runtime systems of a novel search engine tailored for agentic AI consumption.

In this role, you will focus on building low-latency, high-throughput systems that serve search queries in real time. You will work on the critical path of user-facing requests, where performance, predictability, and efficiency directly impact product quality. You will design and operate systems that handle thousands of requests per second under strict latency budgets, optimising every layer from request handling to data access and response assembly.

In this position, your responsibility will be to

• Design, implement, and operate core runtime services for serving search queries at scale
• Build and optimise request flows, including query processing, retrieval orchestration, and response assembly under strict latency budgets
• Develop systems that maintain performance and predictability under high load
• Optimise CPU, memory, and data access patterns in performance-critical paths
• Ensure reliability, observability, and predictability across production services
• Build well-tested systems with clear responsibilities and interaction contracts, while remaining flexible as architecture evolves
• Define and implement observability primitives, including structured logs, metrics, traces, and latency breakdowns
• Monitor throughput, latency, and resource usage, and drive improvements in performance and cost efficiency
• Collaborate with indexing and ML teams to integrate retrieval and ranking components, keeping ML logic decoupled from core system internals
• Support experimentation and iteration through controlled rollouts and rigorous benchmarking

You may be a good fit if you:

• Have 5+ years of experience as a software engineer working on production backend systems
• Have strong hands-on expertise in C++ or Rust in real-world, high-load services
• Have built and operated high-load, low-latency user-facing systems handling thousands of RPS under strict latency constraints
• Understand performance at a systems level — CPU, memory, networking, and data access
• Have operated your own code in production: deployed it, debugged incidents, and rolled back changes when necessary
• Think end-to-end about request flows rather than staying within isolated components
• Can balance correctness, latency, and development velocity, making pragmatic tradeoffs when scope or time requires
• Collaborate effectively across engineering, ML, and product teams, communicating clearly in cross-functional settings

Strong candidates may also have experience with:

• DBMS internals (open source or SaaS) and cloud infrastructure
• High-load web applications or large-scale APIs
• Performance-critical systems such as trading platforms or real-time data pipelines
• Low-level performance tuning and hardware-level optimisation
• Open-source contributions or active involvement in the engineering community
• Competitive programming or CTF participation
• SHAD or similar advanced technical programmes
• Conference talks or technical publications

We conduct coding interviews as part of the process.

The role

Nebius is searching for a Enterprise Networks Engineer with strong automation skills to design, implement, and optimize enterprise networks, including wired, wireless, and VPN infrastructure. 

Your responsibilities will include: 

• Lead the design, implementation, and optimization of enterprise wired and wireless networks, ensuring scalability, security, and high availability
• Own and maintain network connectivity between branch offices around the world, partnering with global teams to standardize architecture and operations
• Manage and ensure the reliable operation of remote access systems (VPN), including capacity planning, resiliency, and continuous improvements
• Deploy, maintain, and continuously improve automation and monitoring tools; define best practices and drive automation-first operations
• Diagnose and resolve complex network issues, including cross-region and cross-provider incidents; perform root cause analysis and implement preventative measures
• Test, evaluate, and introduce new equipment and emerging technologies; contribute findings and recommendations into global R&D streams
• Collaborate with telecom service providers globally; lead escalations, manage SLAs, and drive service improvements

We expect you to have: 

• In-depth knowledge of TCP/IP technologies
• Familiarity with dynamic routing protocols
• Experience in automation using Python, Go, or other popular programming languages (ability to design and maintain production-grade automation)
• Proficiency in Unix system administration
• Hands-on experience with enterprise-grade network hardware (e.g., Cisco, Aruba, Arista, Extreme, Juniper)
• Strong ability to work independently, owning outcomes end-to-end in a senior/lead capacity

It will be an added bonus if you have: 

• Experience with network automation frameworks like Ansible, Terraform, NetBox, Nornir, or SaltStack
• Experience designing, developing, and operating high-load distributed systems
• Experience building high-density enterprise wireless networks (CWNA level or higher)
• Working knowledge of IPv6

The Role

Your responsibilities will include:

• Ensure fault-tolerance, scale, and uninterrupted operations for the service.
• Use cutting-edge cloud technology to solve a variety of infrastructure problems.
• Implement and improve CI/CD processes.

We expect you to have:

• Solid experience with programming languages (like Go, Python, or C++);
• Solid understanding of classic algorithms and data structures;
• Commercial experience with and deep understanding of Unix systems and network technology;
• Experience with systems for containerization and configuration management (Ansible, Salt, Terraform, Docker, K8s, Helm).

It will be an added bonus if you have:

• Desire to be involved in backend development;
• Experience designing, developing, and running high-load distributed systems;
• Commercial experience with a variety of cloud platforms.

We conduct coding interviews as part of the process.

The role

Token Factory is a part of Nebius Cloud, one of the world's largest GPU clouds, running tens of thousands of GPUs. We are building a high-performance inference and fine-tuning platform designed to push foundation models to their hardware limits. Our mission is to maximize throughput, minimise latency, and optimise cost-per-token across tens of thousands of GPUs.

Some directions we are currently working on, and which you can be a part of:

• Inference Optimization: Identifying LLM inference bottlenecks to drive production speedups. Squeezing the maximum performance for a wide range of LLM architectures at scale (e.g., GPT-OSS, Kimi K2.5, DeepSeek V3.1/V3.2, GLM-5).
• Inference engines support: Implement novel speculative decoding architectures, optimise components of various LLM designs (dense/MoE, autoregressive/parallel), and contribute to open-source inference engines.
• Low Precision Training & Inference: Design and productionise low-precision (FP8, NVFP4/MXFP4) training and inference pipelines with measurable gains in throughput and cost-efficiency.

We expect you to have:

• A profound understanding of theoretical foundations of machine learning and transformer architecture.
• Experience profiling GPU workloads using Nsight, PyTorch profiler, or similar tools
• Understanding of GPU memory hierarchy and compute/memory tradeoffs
• Familiarity with important ideas in LLM space, such as MHA, RoPE, KV-cache, Flash Attention, and quantisation
•  Understanding of performance aspects of large neural network training (sharding strategies, custom kernels, hardware features etc.)
•  Strong software engineering skills (we mostly use Python)
• Deep experience with modern deep learning frameworks
• Proficiency in contemporary software engineering approaches, including CI/CD, version control and unit testing
• Strong communication and leadership abilities

Nice to have:

• Experience working with open-source inference engines (vLLM, SGLang, TensorRT-LLM), including contributions
• Experience with kernel languages or DSLs such as Triton, Cute, CUTLASS, CUDA
• A track record of building and delivering products (not necessarily ML-related) in a dynamic startup-like environment.
• Strong engineering skills, including experience in developing large distributed systems or high-load web services.
• Open-source projects that showcase your engineering prowess
•  Excellent command of the English language, alongside superior writing, articulation, and communication skills.

The role

Token Factory is a part of Nebius Cloud, one of the world’s largest GPU clouds, running tens of thousands of GPUs. We are building an inference & fine-tuning platform that makes every kind of foundation model — text, vision, audio, and emerging multimodal architectures — fast, reliable, and effortless to train & deploy at massive scale.

• Advanced Fine-Tuning: Enhancing fine-tuning methodologies - both LoRA-based and full-parameter - for cutting-edge LLMs (e.g., GPT-OSS, Kimi K2.5, DeepSeek V3.1/V3.2, GLM-4.7), focusing on both model quality and training efficiency.

• Inference Optimization: Identifying LLM inference bottlenecks to drive production speedups. This involves building model training and evaluation pipelines in JAX for speculative decoding, experimenting with architectures (dense/MoE, auto-regressive/parallel), and deriving scaling laws to guide resource allocation.                                                                                
• Low Precision Training & Inference: Investigating low-precision (FP8, NVFP4/MXFP4) methodologies for supervised fine-tuning and reinforcement learning - spanning both inference and training - optimized for modern hardware

We expect you to have:

• A profound understanding of theoretical foundations of machine learning and reinforcement learning.

• Deep expertise in modern deep learning for language processing and generation

• Experience with training large models on multiple computational nodes

• Reasonable understanding of performance aspects of large neural network training (sharding strategies, custom kernels, hardware features etc.)

• Strong software engineering skills (we mostly use Python)

• Deep experience with modern deep learning frameworks (we use JAX)

• Proficiency in contemporary software engineering approaches, including CI/CD, version control and unit testing

• Strong communication and leadership abilities

Nice to have:

• Previous experience working with language models or other similar NLP technologies.

• Familiarity with important ideas in LLM space, such as MHA, RoPE, ZeRO/FSDP, Flash Attention, quantization

• A track record of building and delivering products (not necessarily ML-related) in a dynamic startup-like environment.

• Strong engineering skills, including experience in developing large distributed systems or high-load web services.

• Open-source projects that showcase your engineering prowess

• Excellent command of the English language, alongside superior writing, articulation, and communication skills.

We are seeking a Senior Applied ML Engineer to join a fast-growing team building an agent-native search platform for AI systems, the emerging web access layer for AI. You will develop and deploy machine learning models that power retrieval, ranking, and indexing at scale, helping AI systems access fresh, reliable information in real time. This is a high-impact role working on a production system used 24x7, tackling challenges comparable to large-scale web search.

Your responsibilities:

• Design, train, and deploy ML models for retrieval, reranking, and search relevance in production
• Build and optimise embedding-based indexing and large-scale retrieval systems
• Develop models supporting crawling, data selection, and content understanding
• Define and improve quality metrics for agent-native search and build evaluation pipelines
• Work on systems operating at very large scale, including high-throughput query workloads
• Collaborate closely with engineering teams to integrate ML models into production services
• Analyse performance trade-offs across latency, quality, and cost
• Experiment with and apply state-of-the-art techniques in search, retrieval, and LLM-integrated systems
• Contribute to product and architectural decisions in a fast-moving environment

Must-haves:

• 5+ years of experience in software engineering or applied machine learning
• Strong programming skills in Python, Go, or C++
• Proven experience deploying ML models in production systems
• Hands-on experience with retrieval, ranking, recommendation, or similar ML problems
• Strong understanding of machine learning and modern deep learning techniques
• Experience working with large-scale data systems and high-throughput environments
• Ability to design evaluation frameworks and define meaningful model metrics
• Product-oriented mindset with a focus on impact and iteration
• Strong problem-solving skills and ability to work in a distributed team

Nice-to-haves:

• Experience with search systems or large-scale information retrieval
• Familiarity with embeddings, transformers, and modern NLP systems
• Experience working on LLM-powered or agent-based systems
• Contributions to open-source projects, technical publications, or conference talks
• Participation in competitive ML (e.g. Kaggle) or similar signals of strong technical ability

We conduct coding interviews as part of the process.