Boomi provides the foundation on which your business can evolve and innovate. According to a recent survey by Vanson Bourne, connected businesses are far outpacing their competitors. We help organizations connect everything and engage everywhere across any channel, device or platform. More than 7,000 organizations are using Boomi to run better, faster and smarter.

Working at Boomi means doing what you love. We hire trailblazers with an entrepreneurial spirit who can solve challenging problems, make a real impact in technology and want to build something big. If you are passionate about solving hard problems, enjoy working with world-class people and developing cutting edge technology, you should explore a career with Boomi. Learn more at http://www.boomi.com/  or visit Boomi Careers.

Here in Boomi Professional Services, we pride ourselves on our industry leading expertise, high quality delivery and outstanding customer experience that leads to the “right first time” fast time to value service that our customers receive. This is a key reason why customers choose Boomi and Boomi Professional Services. In this role, you will implement the Boomi platform and develop Boomi integrations and APIs for our customers. Join us to do the best work of your career and make a profound social impact as a Boomi Integration Platform Developer in our Professional Services team.

Location: Spain/UK/Germany/France/Netherlands

Key Responsibilities  

As a Boomi Integration Platform Developer you will be supporting Boomi Platform implementation remotely for the clients based all over Europe, Middle East and Africa region. Travelling of up to 20% of the work time might be required. 

Your core duties will include, but are not limited to:  

• Working closely with Project Managers from the region to design and develop integration solutions. 

• Evaluating customer applications to assess integration approach. 

• Being a product expert of Boomi applications including the AtomSphere integration platform and learning other parts of the Boomi platform. 

• Recommending best practices for implementing, managing, and governing integrations using the Boomi AtomSphere integration platform. 
• Defining and promoting the adoption of best practices of Boomi's products across the internal and external user community. 
• Providing support and coaching to junior team members.

Essential requirements   

• Multiple years of experience working with enterprise integration tools, middleware technologies, and application and data integration patterns including JMS, SOAP/REST web services, databases. 

• Practical experience implementing services-oriented architecture design and enabling technologies including messaging, XML, JSON, web services, and HTTP. 

• Advanced knowledge of common business systems (CRM, SFA, ERP) and processes (lead to cash, requisitions, order management, etc.) 

• General knowledge of key application infrastructure components such as VMware, storage (NAS, SAN, SMB), Java JVM, networking (firewall, load balancing, proxies). 

• Good communication and interpersonal skills combined with fluent knowledge of written and spoken English. 

Desirable requirements  

• Database skills including SQL, data modelling, and databases (e.g. MS SQL Server, MySQL, Oracle).

• Development scripting skills with Java, Groovy, JavaScript.

• 1 year plus experience using the Boomi platform would be advantageous.
• Experience working in a professional services consulting business / working directly with customers.
• Experience providing coaching and support to junior team members.

• Additional language capabilities other than English.

What you’ll achieve

As a Consultant you will work closely with customers to understand their requirements, assist with project scoping and build innovative solutions to solve business problems. You’ll have the opportunity to learn more about the Boomi platform and grow your skills as a developer/consultant. You will be joining Boomi at an exciting time of growth and innovation.

#LI-LM1

Nixxes Software is an industry-leading Dutch company specializing in video game design, development and porting.

Working alongside global partners since 1999, our work is fueled by a love for gaming and commitment to innovation. Our Utrecht based team prides itself on delivering the best possible experience for every gamer, regardless of platform. In July 2021 Nixxes joined PlayStation Studios to focus on delivering the highest-quality gameplay experiences for PlayStation fans.

Junior DevOps Engineer 

For our studio in Utrecht, the Netherlands, we're looking for a versatile, pro-active and friendly DevOps programmer to improve the productivity of our project teams with tools and technology.

Responsibilities

• Develop and maintain tools and services

• Set up and maintain CI/CD systems

• Provide technical assistance to team members

• Collaborate closely with our teams and other DevOps staff

Essential Requirements:

• A pragmatic, hands-on, problem-solving mentality

• Basic programming experience in C# or C++

• Basic knowledge of web application development

• Understanding of CI/CD concepts

• Experience with one or more scripting languages

• Self-motivated and pro-active

• Good communication skills in written and spoken English

• Must live in the Netherlands in order to work frequently in the office

Pluses:

• Game industry & development experience

• Experience with Angular and Laravel web frameworks

• Experience with Jenkins automation server

• Interest in the technical aspects of AAA game development

• (Native) Dutch speaker

At Guerrilla, we believe that our team’s varied backgrounds, experiences, and perspectives help us create games that resonate with a diverse audience.

As an equal opportunities employer, we strive to create an inclusive environment, empower employees and embrace diversity.

We encourage everyone to respond as we consider all candidates on the basis of their merit, unique strengths, and perspectives they will bring to the role.

Please refer to our Candidate Privacy Notice for more information about what personal information we collect, how we use it, who we share it with, and your data protection rights. 

Available Locations: London (hybrid), the Netherlands (remote), Paris, or Munich

About the Role

Cloudflare’s Forward Deployed Engineers (FDEs) operate at the intersection of product engineering and customer impact.

As an FDE, you will be embedded within one of Cloudflare’s most strategic global customers, working side-by-side with their engineering teams to build and deploy solutions using Cloudflare’s platform. Unlike traditional Solutions Architects or consultants, you will write production code, shape technical architecture, and directly influence how Cloudflare products are used at massive scale.

You will operate as a technical extension of both organizations - helping the customer ship faster while surfacing real-world product insights back to Cloudflare engineering.

This role is ideal for engineers who want to:

• Stay deeply technical
• Work on real production systems
• Influence product direction
• Build long-term partnerships with world-class engineering teams

Responsibilities

• Deep Technical Embedding: Serve as the dedicated, long-term technical partner within a strategic customer’s engineering organization, operating as a trusted extension of their team.
• Production-Level Engineering: Design, build, and deploy production-ready code and configurations directly into customer infrastructure using the Cloudflare platform.
• Technical Accountability: Own the account's technical success across the entire Cloudflare portfolio. Serve as the primary technical point of contact, with other Cloudflare technical resources taking direction from your technical strategy for the account.
• Operational Integration: Participate in customer engineering rituals, including daily standups, design reviews, and real-time incident response.
• Platform Advocacy & Adoption: Identify opportunities to accelerate the adoption of Cloudflare services, unlocking new capabilities across the customer’s tech stack.
• Platform Breadth & Depth: Deep technical competence in building production applications on a modern stack, combined with the willingness and ability to go deep on all Cloudflare product areas. From Workers to security, networking, and observability.
• Feedback Loop & Product Influence: Surface real-world edge cases and product gaps directly to Cloudflare’s Product and Engineering teams to influence the developer platform roadmap.
• Strategic Relationship Management: Establish and maintain trusted technical relationships with senior leadership (Staff+ engineers, Directors, and VPs).
• On-Site Presence: Maintain a regular on-site presence at customer locations to foster deep collaboration and cultural alignment.

Requirements

• Proven Engineering Pedigree: 5+ years of professional software engineering experience. You are a builder at heart, with a track record of delivering production-grade systems, not just advising on them.
• Production Ownership & Operational Maturity: You have owned mission-critical services with real-world users. You understand the gravity of on-call rotations, the urgency of incident response, and the architectural rigor required to maintain "five nines" uptime.
• Active Practitioner: You are currently in the IDE. You have a "ship-first" mentality and maintain a high velocity, staying current with modern frameworks, languages, and deployment patterns.
• Full-Stack Architectural Depth: Broad technical fluency across the entire stack—from frontend performance and backend logic to database optimization and distributed infrastructure.
• AI-Native Development: You have integrated AI-augmented workflows (e.g., Windsurf, OpenCode) into your daily development cycle to accelerate prototyping and delivery.
• Systems Design & Strategic Thinking: Ability to decompose complex business requirements into scalable, resilient technical architectures. You can visualize the "big picture" without losing sight of the implementation details.
• Cloud Ecosystem Fluency: Deep experience with at least one major cloud provider (AWS, GCP, or Azure), including an understanding of serverless, networking, and security primitives.
• High Agency & Navigating Ambiguity: You are a self-starter who thrives in "zero-to-one" environments. You don't wait for a ticket; you identify the problem and own the solution from end-to-end.
• Executive Presence: Comfortable engaging in high-stakes technical and strategic discussions with VP-level stakeholders, with the ability to translate complex engineering trade-offs into business impact.
• Fluency in Hebrew and English

Nice to Have

• Direct experience building on Cloudflare Workers, or the broader Cloudflare Developer Platform.
• Previous experience at a fast-paced startup or in a customer-facing engineering role where you operated directly within a partner’s codebase.
• A visible public profile, including open-source contributions, technical blogging, or speaking engagements at industry conferences.

• 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

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

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

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.

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

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 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

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.

• 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

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.

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.

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 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

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.

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

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

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.

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.

• 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!

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.

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!

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!

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

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

The role

Nebius is looking for a Senior Software Engineer in Hardware Infrastructure team. You’re welcome to work in our office in Amsterdam.

Hardware Infrastructure team designs, develops and supports systems involved in the data center lifecycle.

Your responsibilities will include:

Design and develop services that automate work with a large server fleet

We expect you to have:

• 5+ years of professional software engineering experience
• Excellent knowledge of Python or Golang, or you are ready to quickly switch to these programming languages
• Ability to write reliable code and dig into complex problems
• Strong interest in being engaged in DevOps processes
• Working proficiency in English

It will be an added bonus if you have: 

• Solid understanding of modern server architecture and its components
• Good knowledge of computer networks
• Experience designing, developing and running high-load distributed systems

The Role

Nebius is looking for a Senior Software Engineer to join the Hardware Infrastructure Observability team. You're welcome to work from our office in Amsterdam. We build and run low-level monitoring for servers and data center engineering systems to ensure reliability at scale. We also design and operate maintenance and remediation systems that enable safe, predictable fleet-wide changes and keep the infrastructure healthy.

Key Responsibilities:

• Design and develop services and agents that provide deep visibility into a large server fleet and DC engineering systems
• Evolve our metrics/aggregation/alerting pipelines and improve signals quality
• Build maintenance workflows and automation that keep fleets healthy
• Investigate incidents hands-on (including on-host debugging) and drive root-cause fixes
• Collaborate with hardware, networking, and DC operations to improve reliability
  

We expect you to have:

• 5+ years of professional software engineering experience
• Excellent knowledge of Python and Golang or you are ready to quickly switch to these programming languages
• Strong Linux fundamentals
• Ability to write reliable code and and dig into complex problems
• Working proficiency in English

It will be an added bonus if you have: 

• Solid understanding of modern server architecture, and its components
• Experience with metrics/monitoring/alerting Prometheus-compatible stacks (like VictoriaMetrics)
• Good knowledge of computer networks
• Experience designing, developing, and running high-load distributed systems

We conduct coding interviews as part of the process.

The role 

We are looking for a dynamic Supply Chain Manager to join our growing team in Amsterdam, The Netherlands. If you possess strong analytical and organizational skills, easy-going and keen for developing in an IT company we invite you to apply for this exciting opportunity.

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

Your responsibilities will include: 

• Processing local purchases: the whole circle starting from receiving the task with description and lead time to receiving the goods at the location (Europe).
• Managing existing suppliers and extend the local suppliers database.
• Driving cross-functional collaboration: several teams are involved into the process (IT/engineer, purchase, finance, logistics).
• Creating dashboards and report on existing tasks to ensure all tasks are done in a timely manner within the deadline.

We expect you to have: 

• Experience in IT purchases or a related role with existing IT hardware suppliers network.
• Working proficiency in English.
• Strong analytical and problem-solving skills with a data-driven mindset.
• Good skills of time management, prioritizing tasks and meeting deadlines.
• Good communication skills.
• Advanced experience with Outlook and MS Office.

It will be an added bonus if you have: 

• Understanding of Netsuite.

Why it matters:
This is a rare opportunity to step in at a formative moment — to shape the systems and processes that will define how we scale. It’s a high-impact role, visible across the company, and essential to our success.

The role

The Compute Node team builds services for managing Virtual Machines running on GPU servers, integrating with disk management, virtual and InfiniBand networks. The team is also responsible for developing the Virtual Machine Scheduler that operates across clusters with thousands of servers and tens of thousands of GPUs, spanning multiple data centers in several regions.

We expect you to have: 

1. Containerization & Orchestration

• Experience with Kubernetes not only for deployment but for development is highly valued.

2. Virtualization

• KubeVirt and QEMU/KVM familiarity is a high plus.

3. Linux & System-level Understanding

• Solid knowledge of internal OS architecture, performance considerations, process isolation and resource management.

• Knowledge of POSIX, sysfs, system calls, and file systems.

• Familiarity with server architecture, PCIe devices, NICs, and kernel drivers.

4. Hardware Acceleration

• Experience or strong interest in working with GPUs, DPUs, or ARM architectures is desirable.

• Familiarity with the NVIDIA DOCA Software Framework will be an advantage.

5. Go, C++ Proficiency

• Knowledge of at least one of these languages, ready to learn or work with the others as needed.

• Strong grasp of concurrency, debugging, and profiling techniques.

We conduct coding interviews as part of the process.

The role

At Nebius, we’re building a next-generation AI compute platform for large-scale ML training and inference — from a few nodes to thousands of GPUs.
We’re looking for a Technical Product Manager to own product direction for Soperator — our Slurm-on-Kubernetes control plane for GPU clusters.
In this role, you will shape how ML engineers and research teams run, scale, and optimize distributed workloads in production.
If you care about systems that combine performance, reliability, and developer experience at the frontier of AI infrastructure, this role is for you.

Your responsibilities will include: 

• Own the full user journey across Soperator clusters: Slurm workflows, dashboards, alerts/notifications, node lifecycle, and training/inference capacity management.
• Define product direction end-to-end: problem discovery → solution design → delivery → adoption.
• Lead deep customer discovery through interviews, usage analytics, and workload analysis to uncover high-impact opportunities.
• Drive execution across platform teams: compute, networking, storage, observability, IAM and etc.
• Translate frontier ML and infrastructure ideas into practical product capabilities for real-world GPU clusters.
• Define success metrics, prioritize roadmap decisions with data, and ensure measurable customer/business impact.
• Lead the open-source strategy and execution for Soperator: shape public roadmap themes, prioritize OSS-facing capabilities, and ensure strong adoption in the community.  

We expect you to have: 

• 3–5+ years in Product Management, ML infrastructure/MLOps, distributed systems, or cloud platform engineering.
• Strong technical depth in distributed systems, cloud infrastructure, or ML platforms.
• Hands-on familiarity with large-scale ML training and orchestration tools (e.g., Slurm, Kubernetes, Ray).
• Track record of shipping technically complex products with multiple engineering teams.
• Strong communication and stakeholder management across engineering, research, and customers.
• Experience with product analytics, data-informed prioritization, and experimentation.
• High ownership, high learning velocity, and comfort operating in fast-moving AI infrastructure environments.

It will be an added bonus if you have: 

• Experience with GPU platforms and HPC primitives: InfiniBand/RDMA, topology-aware scheduling, high-throughput storage.
• Practical understanding of modern ML training stacks: PyTorch, DeepSpeed, FSDP/ZeRO, NCCL.
• Familiarity with efficiency and reliability metrics: Goodput, MFU, failure modes, preemption handling, health checks.
• Exposure to large-scale LLM training/inference systems.
• Experience in observability, performance tuning, or SRE/reliability engineering.
• Customer-facing technical experience (solutioning, support, architecture advisory).

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. 

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

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.

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.

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 

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 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.  

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

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 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 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 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 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 

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)

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)