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.

Role

We are looking for a Sr. Network and Infrastructure Engineer to join our Cloud Ops - Network Engineering department in a fully remote capacity in the Netherlands, reporting to the Manager, Network Engineering.

This position involves a mix of infrastructure, project management, and network engineering responsibilities. You will drive the design, implementation, and operation of complex network architectures, leading large-scale data center builds and expansions from start to finish with a strong sense of urgency.

What you’ll do (Role Expectations)

• Plan, implement, document, and manage data center cabinet layouts and power density to ensure maximum efficiency and reliability
• Oversee server capacity deployments, integrating infrastructure with automation to support global scalability and optimized resource utilization
• Collaborate with project management and engineering development teams to align on service requirements and hardware integration
• Work across functional teams to ensure the seamless synchronization of hardware, software, and network resources
• Provide expert technical guidance and troubleshooting support for complex data center infrastructure-related issues. This position will have to participate in on-call rotation in weekends and holidays.

Who You Are (Success Profile)

• You thrive in ambiguity. You're comfortable building the path as you walk it and see dynamic environments as the raw material to build something meaningful.
• You act like an owner. Your passion for the mission fuels your bias for action and you navigate seamlessly between high-level strategy and hands-on execution.
• You are a problem-solver. You seek out challenges because you are energized by finding solutions, knowing that solving the hard problems delivers the biggest impact.
• You are a high-trust collaborator. You are ambitious for the team, not just yourself, embracing a challenge culture where candor is delivered with clarity and respect.
• You operate with urgency. You have a relentless focus on execution and a bias for action, delivering high-impact results quickly to win for the customer and the team.

What We’re Looking for (Minimum Qualifications)

• Professional experience in remote data center operations, including device configuration and debugging fiber and patching issues
• 2-5 years of experience working with high-speed networks ranging from 10G to 100G and beyond
• Hands-on experience in BGP routing operations and troubleshooting for both IPv4 and IPv6 in large-scale environments
• Proven organizational skills with experience managing complex priorities within problem ticketing and inventory systems
• Bachelor’s Degree in Engineering or equivalent professional experience

What Will Make You Stand Out (Preferred Qualifications)

• Experience with Linux/Unix environments and proficiency in writing Unix shell scripts
• Technical knowledge of DNS, HTTPS, GRE, and IPsec protocols with practical troubleshooting experience
• Ability to automate end-to-end deployments at scale to drive operational efficiency

#LI-REMOTE

#LI-MM8

Role

We are looking for a Staff Data Center Operations Engineer to join our Network Infrastructure department on-site near Schipol Airport, Amsterdam, reporting to the Datacenter Deployment Manager.

In this position, you will play a critical role in expanding Zscaler’s global cloud by utilizing automation to provision hardware that will be deployed to our data centers.

What you’ll do (Role Expectations)

• Provision new hardware and network devices in a staging environment that will be deployed globally to expand and supplement the Zscaler network
• Troubleshoot issues within our build environment and repair or replace server and network components and infrastructure
• Collaborate with the maintenance, network, install and platform engineering teams to execute and validate build activities and assist in optimizing processes

Who You Are (Success Profile)

• You are a positive force. You approach hard problems with constructive energy and a 'can-do' spirit that is contagious, inspiring your team to stay focused on the solution.
• You operate with urgency. You understand that in a high-growth environment, speed and quality are not mutually exclusive. You have a relentless focus on execution and a bias for action, delivering high-impact results quickly to win for the customer and the team.
• You are driven by innovation. You have a deep curiosity for how things work and are energized by solving complex technical challenges. You believe in the power of technology to accelerate transformation and are always looking for a better, more secure, and scalable way.
• You champion simplicity. You are skilled at distilling complex problems, user needs, and technical concepts into clear, simple, and actionable plans. You are a precise communicator who brings clarity and focus to every interaction.
• You are resilient and adaptable. You view change as an opportunity and setbacks as temporary. You maintain composure and focus in high-pressure situations, guiding yourself and your team through complexity with a steady, positive hand.

What We’re Looking for (Minimum Qualifications)

• Experience working in Data Center or hardware build and development environments
• Deep understanding of various types of servers, network devices and configurations, and physical connectivity
• Proficiency with the LINUX/UNIX command line, BIOS, and OOB management tools such as ILO, SAA, iDRAC, or IPMI

What Will Make You Stand Out (Preferred Qualifications)

• Basic scripting capabilities in BASH or Python
• Familiarity with build automation technologies such as Ansible or PXE boot
• Experience with Jira, Confluence, or other ticketing and documentation tools

#LI-MM8

#LI-ONSITE

Your future role within QRT:

We are hiring a Senior Low-Latency Software Engineer to join a newly formed team building a high-performance trading platform from scratch.

This platform sits at the heart of QRT’s execution capabilities and is designed for ultra-low-latency, high-frequency trading. You will work on systems where performance is critical, contributing directly to how strategies are executed in live markets.

You will collaborate closely with quant researchers and traders to turn models into efficient, production-grade systems, while shaping the architecture and performance of the platform using modern C++ (C++23).

Responsibilities:

• Design, build, and optimize greenfield, high-performance distributed trading systems in C++, with a strong focus on latency, scalability, and reliability
• Partner closely with quant researchers and trading teams to translate strategies into production systems and contribute to the overall architecture

Your present skillset:

• 5+ years of experience in low-latency / high-performance C++ development
• Strong expertise in modern C++ (C++17/20/23) and systems programming
• Experience with multithreading, concurrency, and real-time systems
• Solid understanding of Linux systems and low-level performance optimization

Nice to have:

• Experience in electronic trading systems (market data, execution, or connectivity)
• Understanding of market microstructure
• Knowledge of networking (TCP/UDP) and system-level performance tuning
• Exposure to hardware acceleration (e.g. FPGA)
• Experience with Python for tooling or prototyping

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.

Summary:

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

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

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

Your responsibilities will include

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

What we offer

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

We’re growing and expanding our products every day. If you’re up to the challenge and are excited about AI and ML as much as we are, join us!

The role

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

Your responsibilities will include: 

• Develop… 

• Collaborate with… 

• Manage…  

We expect you to have: 

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

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

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

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

• Familiarity with… 

• Understanding of…  

• Knowledge of… 

• Background in… 

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

• Working knowledge of spoken and written English 

It will be an added bonus if you have: 

About Nebius

Nebius AI is an AI cloud platform with one of the largest GPU capacities in Europe. Launched in November 2023, the Nebius AI platform provides high-end, training-optimized infrastructure for AI practitioners. As an NVIDIA preferred cloud service provider, Nebius AI offers a variety of NVIDIA GPUs for training and inference, as well as a set of tools for efficient multi-node training. 

Nebius AI owns a data center in Finland, built from the ground up by the company’s R&D team and showcasing our commitment to sustainability. The data center is home to ISEG, the most powerful commercially available supercomputer in Europe and the 16th most powerful globally (Top 500 list, November 2023).  

Nebius’s headquarters are in Amsterdam, Netherlands, with teams working out of R&D hubs across Europe and the Middle East. 

Nebius AI is built with the talent of more than 500 highly skilled engineers with a proven track record in developing sophisticated cloud and ML solutions and designing cutting-edge hardware. This allows all the layers of the Nebius AI cloud – from hardware to UI – to be built in-house, distictly differentiating Nebius AI from the majority of specialized clouds: Nebius customers get a true hyperscaler-cloud experience tailored for AI practitioners. We’re growing and expanding our products every day. 

If you’re up to the challenge and are excited about AI and ML as much as we are, join us!

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

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

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

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

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

Your responsibilities:

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

Must-haves:

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

Nice-to-haves:

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

We conduct coding interviews as part of the process.

The role

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

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

We expect you to have:

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

It would be an added bonus if you had:

• Experience designing high-load and scaling services

We conduct coding interviews as part of the process.

The role

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

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

We expect you to have:

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

It would be an added bonus if you had:

• Experience designing high-load and scaling services

We conduct coding interviews as part of the process.

The role

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

In this position, you will be responsible for:

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

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

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

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

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

We expect you to have:

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

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

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

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

It would be a plus if you have:

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

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

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

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

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

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

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

We conduct coding interviews as part of the process.

The role

Your responsibilities will include:

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

Required Skills & Qualifications: 

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

It will be an added bonus if you have:

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

• 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 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.

The Role

Your responsibilities will include:

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

We expect you to have:

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

It will be an added bonus if you have:

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

We conduct coding interviews as part of the process.

The Role

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.

• 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!

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 

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.