Role & Team

As a Data Engineering Manager, you will lead across several cross-functional teams, managing up to ~10 data engineers and GIS specialists. You will support teams working on data processing and pipelines to enable ML-powered product capabilities.

Our product teams are cross functional and will typically include product managers, designers, engineers and subject matter experts relating to the team’s domain.

You will be accountable for the technical direction and delivery outcomes of your area. You will challenge your teams to pursue ambitious goals while providing a high level of support — growing engineering talent and fostering a highly collaborative, team-based environment where people can do great work.

Your primary focus will be on building high-performing teams and driving results through others. You will not be expected to spend significant time doing hands-on coding; however, you will be expected to dive deep technically when required and leverage your experience to support strong technical decision-making.

Time zone requirement: Europe (GMT/WET, CET, EET) and Eastern North America (NST, AST, EST)

What You'll Do

• Enable our data engineers to become highly productive members of their cross-functional teams, empowering them to ship high-quality, reliable data platforms and pipelines on a daily basis.
• Grow the teams by attracting great talent from your network.
• Foster an inclusive and caring culture where everyone can do their best work.
• Provide regular 1:1 coaching and feedback to tap into the potential of all your team members and help them thrive and reach their aspirations.
• Be a strategic partner to product managers, machine learning engineers, and other stakeholders within your domains and ensure that we are making the correct data architecture and platform decisions that balance short and long term goals.
• Ensure suitability of the data architecture, pipelines, and data models within your domains to enable longer term product, analytics, and machine learning goals.
• Work closely with the other Product & Engineering leaders on strategy, technology and people, including improving our data engineering practices and introducing capabilities that can accelerate data access, reliability, and unlock new product and data-driven opportunities

Skills & Experience

• Experience working in a high growth scaleup environment
• Passionate about climate
• Product minded and able to demonstrate significant impact you have had on a business through the application of data platforms and data-driven systems
• 2+ years experience leading and managing data engineers across multiple teams
• Experience working with the following (or similar) technologies: Python, SQL, data pipeline orchestration tools (e.g., Airflow, Dagster), data warehouses/lakehouses, Postgres DB, data pipelines
• Ability to unblock your team by contributing at a senior engineering level (e.g., reviewing data models, debugging pipelines, guiding architecture). How hands-on you'll be in this role will depend on team size and maturity
• Comfortable working in a build it, run it environment (GCP, cloud run, grafana, k8s) - or similar, with an understanding of data reliability, observability, and pipeline operations
• Strong leadership skills with the ability to mentor and coach engineers at all levels
• Excellent communication skills and ability to collaborate effectively in a cross-functional team environment
• Passion for learning and staying updated with evolving technologies and industry trends, particularly in data engineering and data infrastructure

Nice To Have

• Experience working with maps/imagery/geospatial domains  

Note: We believe that all people are capable of great things. We encourage you to apply even if you do not meet all of the requirements that are listed within this job description.

What We Offer

• Competitive, location-specific compensation and benefits 
• Flexible, autonomous and collaborative working environment rooted in trust - we build our work days around our lives, not the other way around
• Home office stipend, coworking and ongoing education budgets 
• A company culture that genuinely embodies each of our core values
• To be part of truly mission-driven work that reduces wildfires, protects earth’s natural resources and helps solve our climate crisis

Role & Team

As an ML Engineering Manager, you will lead across several cross-functional teams, managing up to ~10 machine learning engineers and data scientists. You will support teams working on data- and machine-learning-driven product capabilities.

Our product teams are cross functional and will typically include product managers, designers, engineers and subject matter experts relating to the team’s domain.

You will be accountable for the technical direction and delivery outcomes of your area. You will challenge your teams to pursue ambitious goals while providing a high level of support — growing engineering talent and fostering a highly collaborative, team-based environment where people can do great work.

Your primary focus will be on building high-performing teams and driving results through others. You will not be expected to spend significant time doing hands-on coding; however, you will be expected to dive deep technically when required and leverage your experience to support strong technical decision-making.

Time zone requirement: Europe (GMT/WET, CET, EET) and Eastern North America (NST, AST, EST)

What You'll Do

• Enable our Machine Learning and data teams to operate as highly productive, cross-functional teams delivering high-quality ML-driven capabilities
• Support teams working with satellite imagery and geospatial datasets, balancing experimentation, iteration, and ongoing improvement of existing solutions
• Grow the teams by attracting and hiring great Data and ML talent
• Foster an inclusive, supportive, and caring culture where everyone can do their best work
• Provide regular 1:1 coaching and feedback to help others thrive, grow, and reach their aspirations
• Act as a strategic partner to Product Managers within your domains, ensuring technical decisions balance short- and long-term goals
• Ensure the technical approaches within your domains support future product and modelling needs
• Work closely with other Product, Design and Engineering leaders on strategy, technology, and people
• Help evolve Data and ML practices and introduce ways of working that improve collaboration, delivery, and learning

Skills & Experience

• 8+ years of professional experience building ML- or data-driven systems, at least 3 years’ experience leading and managing ML or data-focused teams
• Passionate about climate and the role technology can play in addressing environmental challenges
• Experience working in a high-growth scale-up or startup environment
• Product-minded, with the ability to demonstrate meaningful business impact through technology
• Sufficient technical depth in machine learning, data systems, or applied ML to guide teams and challenge decisions
• Experience working with python-based ML or data workflows and collaborating closely with data scientists
• Strong leadership skills, with a coaching mindset and the ability to support engineers and data scientists at all levels
• Excellent communication skills and the ability to collaborate effectively in cross-functional environments
• Passion for learning and staying current with evolving technologies and industry trend

Nice To Have

• Engineering mindset or background, with experience applying software engineering best practices to data and ML systems (e.g., reproducibility, testing, monitoring, and production deployments)

Note: We believe that all people are capable of great things. We encourage you to apply even if you do not meet all of the requirements that are listed within this job description.

What We Offer

• Competitive, location-specific compensation and benefits 
• Flexible, autonomous and collaborative working environment rooted in trust - we build our work days around our lives, not the other way around
• Home office stipend, coworking and ongoing education budgets 
• A company culture that genuinely embodies each of our core values
• To be part of truly mission-driven work that reduces wildfires, protects earth’s natural resources and helps solve our climate crisis

As a Data Analyst at Guerrilla, you will turn player and gameplay data into actionable insights that support data-informed decision-making across development teams. Working closely with designers, producers, engineers, and user research, you will investigate player behaviour, contribute to analytical approaches, and communicate insights that support game development.

What You Will Do

Your responsibilities will include:

• Support analytics for one or more gameplay domains (e.g., progression, combat systems, economy, player onboarding), working with stakeholders to define goals, measurement approaches, and analysis plans.
• Conduct analyses that uncover player behaviour patterns, design risks, and opportunities to improve engagement and player experience.
• Partner with cross-disciplinary stakeholders (design, production, engineering, user research, publishing) to shape analysis from question framing through delivery and follow-up.
• Help define success metrics by translating project goals into KPIs, standard metrics, and measurement approaches that are practical for development teams.
• Contribute to the design and validation of gameplay telemetry and event taxonomy to ensure analytics can effectively measure player behaviour and game systems.
• Ensure data quality and trust by monitoring data completeness, consistency, and reliability, and clearly communicating limitations when they exist.
• Translate analyses into clear insights and recommendations that support design, production, and product decisions.
• Support experimentation and measurement efforts for gameplay features, helping teams evaluate feature performance and player impact.

Candidates hired at the Senior level will also be expected to:

• Own analytics initiatives for key gameplay domains and drive analytical investigations that influence development decisions.
• Proactively identify opportunities for analysis and shape analytical roadmaps with cross-disciplinary stakeholders.
• Lead the design and evolution of gameplay telemetry and event taxonomy.
• Guide experimentation and measurement strategies for gameplay features.
• Mentor and support other analysts, contributing to strong analytical practices across the team.

Who You Are

We'd love to hear from you if you have: 

• Experience working with cross-disciplinary teams to deliver analytical insights that support decision-making.
• Advanced SQL skills with a strong track record of working with large behavioural datasets (e.g., event streams / telemetry).
• Strong analytical ability and quantitative reasoning (e.g., distributions, correlations, cohort analysis).
• Experience working with stakeholders to turn ambiguous questions into well-scoped analysis and actionable insights.
• A strong understanding of games and player behaviour.
• Experience with data visualisation tools such as Tableau.
• Strong communication and presentation skills.
• Experience working with gameplay telemetry or instrumentation in complex products.
• Experience with Python (and Jupyter notebooks) or applied ML techniques used pragmatically to solve product or game questions.

Plusses:

• Curiosity and a habit of exploring new analytical methods or tools when appropriate.
• Experience with A/B testing or experimental design.
• Familiarity with version control workflows (e.g., Git) and reproducible analysis practices.

Interested?

If you think you’re up for the challenge, we’d love to hear from you! You can apply by hitting the “apply now” button. Be sure to submit your CV and cover letter.

Please note: This position is based in our studio in the heart of Amsterdam. Guerrilla offers relocation and immigration support.

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

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

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

SLSQ327R42

Note: There is a strong preference for the candidate to be based in Stockholm, though we are open to strong candidates located in Denmark or Finland.

Want to help solve the world’s toughest problems with data and AI? This is what we do every day at Databricks.Databricks operates at the leading edge of the Data and AI space. Our customers turn to us to lead the accelerated innovation their businesses need to gain first-mover advantage in today’s ultra-competitive landscape.

As a Core Enterprise Account Executive, you will own a focused territory of ~10 large Enterprise spending accounts across the Nordics. As a successful candidate, you are a high-achieving sales professional and self-starter who understands the consumption sales process. You know how to sell innovation and value to existing customers, are always prospecting and identifying new use cases and growing consumption, and can guide deals forward to compress decision cycles. You love understanding a product in-depth, and are passionate about communicating its value to customers and partners. You will report to the Director of Enterprise Sales, Nordics. 

The impact you will have:

• Assess your territory and develop a successful execution strategy 
• Drive quarter-on-quarter consumption growth in existing accounts
• Exceed activity and quarterly revenue targets
• Track all customer details including use case, purchase time frames, next steps, and forecasting in Salesforce
• Identify new use case opportunities and showcase value to existing customers
• Promote the value of the Databricks' Data Intelligence Platform 
• Ensure 100% satisfaction among all customers

What we look for:

• Minimum 4+ years of sales experience in the software industry, preferably in open source, data platform, AI/ML Infra, Observability, cloud infrastructure or cloud security 
• Experience growing consumption, and closing commit deals in a direct sales role
• Proven track record of exceeding sales targets/quotas
• Advanced understanding of MEDDPICC and Value Selling
• Competent with prospecting research and ability to map out key stakeholders
• Business fluency in English and a Nordic language is required
• Bachelor's Degree or relevant work experience

Description

The People Systems team plays a critical role in enabling Nebius’ HR organization through technology, managing initiatives that range from end-user support and system administration to scaling the broader HR technology ecosystem as the company grows rapidly.

As a Senior HR Systems Administrator, you will play a key role in ensuring the reliability, scalability, and governance of Nebius’ HR systems landscape, with a primary focus on our HRIS, HiBob. You will act as a senior operational owner within the team, ensuring high-quality service delivery, maintaining system integrity, and supporting the evolution of our People Systems roadmap.

In this role, you will collaborate closely with HR, Recruitment, IT, Finance, and other stakeholders to resolve complex system issues, maintain strong operational processes, and drive initiatives that improve data quality, documentation, and system reliability. You will also serve as a bridge between the HR Systems Administrator and HR Systems Analyst tracks, helping ensure alignment between operational support and strategic system development.

This role offers the opportunity to shape the operational backbone of Nebius’ People Systems function while helping scale the team’s processes, tooling, and governance as the organization continues to grow.

Responsibilities

• Own SLA delivery for People Systems support, ensuring requests are resolved within agreed timelines and proactively removing blockers for the team to prevent SLA breaches
• Provide advanced troubleshooting and end-user support for Nebius’ HR systems (primarily HiBob), developing deep expertise in how stakeholders interact with the platform and resolving complex system issues
• Serve as a bridge between the HR Systems Administrator and HR Systems Analyst tracks, ensuring alignment between operational support work and ongoing system development initiatives
• Drive initiatives to improve HR data quality and system governance, proactively identifying inconsistencies and working with our IT Infrastructure team in designing and implementing controls to prevent data integrity issues
• Partner with IT Infrastructure team to support integrations and monitoring solutions, including contributing to API-based validation and alerting mechanisms that help maintain data integrity
• Identify opportunities to automate manual processes and expand self-service capabilities within HR and Recruitment systems to improve efficiency and scalability
• Maintain clear visibility over support requests and operational initiatives, ensuring work is effectively tracked, prioritized, and documented within the ticketing system
• Identify and close gaps in documentation and operational processes, ensuring knowledge is well organized and accessible within Confluence
• Own and deliver specific initiatives on the People Systems roadmap while acting as a functional lead for other HR Systems Administrators in the absence of the People Systems Manager

Requirements

• Excellent verbal and written communication skills in English
• 7+ years of experience in HR, People Operations, or HR Systems roles, with significant experience in HR systems administration
• Strong hands-on experience working with a modern HRIS platform (HiBob experience preferred but not mandatory)
• Proven experience supporting HR systems in a fast-paced, scaling environment
• Demonstrated experience working with SLAs, ticketing systems (Jira experience preferred), and structured support processes
• Strong analytical and troubleshooting skills with the ability to investigate complex system or data issues
• Experience identifying and implementing automation or process improvements within HR systems
• Practical understanding of APIs, integrations, and webhooks in the context of HR systems
• Experience supporting compliance or (SOX) audit-related processes

• 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

Nebius is seeking a talented Senior Insurance Manager to join our Risk Management team. The role will be responsible for the development, implementation, and ongoing management of Nebius’ global insurance strategy. The role ensures that all company assets, operations, and contractual exposures are adequately protected through effective and efficient insurance programs.

This position plays a critical role in supporting the company’s rapid international expansion, particularly in relation to large-scale AI infrastructure and data center operations.

Your responsibilities will include: 

• Lead the development, placement, and ongoing management of all corporate insurance policies.
• Identify, and assess risks across Nebius’ global assets and operations, with a focus on data center infrastructure
• Ensure that insurance coverage is comprehensive, cost-effective, and aligned with the company’s evolving risk exposure
• Act as the primary point of contact for insurance brokers, insurers, and external advisors
• Map and manage insurance requirements across all jurisdictions in which Nebius operates
• Review and ensure compliance with insurance-related provisions in customer and key vendor contracts
• Oversee and manage insurance claims processes, ensuring timely and effective resolution
• Provide expert guidance and act as the internal focal point for all insurance-related matters across departments
• Continuously evaluate and optimize the company’s insurance strategy in line with business expansion and industry developments

We expect you to have: 

• At least 7 year of experience as a senior/lead insurance within a multinational organization.
• Strong expertise in structuring and managing complex global insurance programs
• Experience in infrastructure, energy, technology, or data center environments is highly preferred
• Deep understanding of international insurance markets, regulatory frameworks, and cross-border risk considerations.
• Proven experience working with brokers, insurers, and external advisors at a strategic level.
• Strong knowledge of contractual risk transfer and insurance requirements
• Excellent stakeholder management, negotiation, and communication skills
• Ability to operate effectively in a dynamic, fast-growing, and international environment

It will be an added bonus if you have: 

• Demonstrates strong ownership and accountability for outcomes.
• Exercises sound judgment in complex and uncertain situations.
• Communicates clearly and translates complexity into business-relevant insights.
• Maintains attention to detail while understanding the broader business context.
• Acts proactively to identify and address risks early.
• Builds collaborative, trust-based relationships in a global environment.

The role

The Senior Internal Communications Business Partner is a newly created role within our growing Internal Communications team, designed to bring dedicated, strategic communications support to key departments such as HR, Finance and Sales. Acting as a trusted advisor and liaison, the Internal Communications Business Partner will develop tailored communication strategies that align with departmental goals and broader organizational priorities.

This role plays a critical part in enhancing clarity, alignment, and engagement across the business by ensuring that communications are audience-focused, timely, and actionable. By working closely with department leads and subject matter experts, the Senior Internal Communications Business Partner helps shape messaging, optimize delivery, and amplify initiatives, ultimately improving understanding, adoption, and impact.

With a strong focus on collaboration, consultation, and execution, this role also reduces the communications burden on leaders by providing expert guidance, crafting communications, and ensuring alignment with internal standards and tone of voice. As part of a new and evolving function, the Senior Internal Communications Business Partner will contribute to building internal communications practices from the ground up, bringing a proactive, solutions-oriented mindset to every partnership.

 Key Responsibilities

• Partner with assigned departments to deeply understand their objectives, challenges, and priorities, translating these needs into effective, audience-specific communication strategies.
• Develop, plan, and execute tailored communication campaigns and initiatives that drive employee engagement, adoption of key programs, and support change management efforts for smoother transitions.
• Serve as a trusted advisor to leaders and stakeholders, offering expert counsel on tone, messaging, timing, and communication approaches to ensure clarity and impact.
• Collaborate closely with subject matter experts to create, review, and edit communication materials that align with the company’s broader communication strategy and brand voice.
• Partner with the Internal Communications team to coordinate campaign delivery and ensure integration and alignment of messages across departments, markets, and teams.
• Build and maintain strong, trusted relationships with stakeholders across multiple markets and teams to foster collaboration, two-way communication, and alignment.
• Provide measurement, feedback, and insights on communication effectiveness using data and employee feedback, adapting strategies to improve reach and engagement continuously.
• Contribute to developing and evolving internal communication frameworks, tools, and processes as part of the growth of the new Internal Communications team.

Key Qualifications & Experience

• Bachelor's degree in Communications, Marketing, Public Relations, Human Resources, Business, or a related field.
• 5+ years of experience in internal communications, corporate communications, or a related advisory role, preferably supporting multiple departments or business units.
• Proven ability to act as a trusted communications advisor to senior leaders and stakeholders, translating complex business needs into clear, impactful communication strategies.
• Strong experience designing, executing, and measuring targeted communication campaigns that drive engagement, adoption, and support change management initiatives.
• Excellent writing, editing, and storytelling skills, with the ability to craft compelling messages tailored to diverse audiences and communication channels.
• Demonstrated collaboration and relationship-building skills, with experience working cross-functionally and managing multiple stakeholders across functions and geographies.
• Data-driven mindset with experience analyzing communication effectiveness and using feedback to continuously improve strategies.
• Solid understanding of communication best practices, tools, and channels.
• Highly organized with strong project management skills, able to balance multiple priorities and deliver high-quality work in a fast-paced environment.
• Adaptable and proactive, comfortable working in a dynamic, evolving team and business context.

The role

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

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

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

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

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

Some examples of what your responsibilities might include are:

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

We expect you to have:

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

Nice to have:

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

About the role:

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

Responsibilities:

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

• Improve performance of inference engines GPU platforms 

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

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

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

Required Qualifications:

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

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

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

• Solid understanding of CPU/GPU architecture and memory hierarchy 

Preferred Qualifications: 

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

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

• Knowledge of Linux internals, drivers, or compiler toolchains 

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

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

We conduct coding interviews as part of the process.

The role

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

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

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

We expect you to have:

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

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

• Experience with training large models on multiple computational nodes

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

• Strong software engineering skills (we mostly use Python)

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

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

• Strong communication and leadership abilities

Nice to have:

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

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

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

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

• Open-source projects that showcase your engineering prowess

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

The role

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

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

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

We expect you to have:

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

Nice to have:

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

The role

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

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

Your responsibilities will include:

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

We expect you to have:

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

It would be an added bonus if you had:

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

The Role

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

Your responsibilities will include:

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

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

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

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

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

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

We expect you to have:

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

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

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

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

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

It will be an added bonus if you have:

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

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

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

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

The role

We are seeking an experienced Product Designer to join our team. You’ll have the opportunity to work from our offices in Amsterdam, Berlin, London or Prague with a hybrid work schedule.

• Own the end-to-end design of services and features within the Nebius Console, from discovery to delivery
• Design clear, scalable interfaces for complex cloud and AI infrastructure products
• Translate business goals, technical constraints, and user needs into coherent user flows and interaction models
• Work closely with Product Managers, Engineers, and other stakeholders throughout the product lifecycle
• Clearly present design solutions and rationale to cross-functional teams
• Manage design work from early hypotheses and exploration through prototyping, implementation, and iteration
• Contribute to the development and maintenance of the design system, ensuring consistency and quality across the product

• Strong product thinking and the ability to approach design as a set of connected user scenarios
• Ability to balance usability, consistency, and innovation in complex systems
• Solid understanding of the product design process, including discovery, validation, and delivery
• High attention to detail and structured, systematic work in Figma
• Experience collaborating with other designers in a shared product and design system environment
• At least 5 years of experience as a Product Designer on digital products
• Confident English communication skills, sufficient for day-to-day collaboration with international teams
• Strong proficiency in Figma, including creating complex and interactive prototypes

• Experience designing responsive and adaptive functional interfaces
• Familiarity with UX research and usability testing methods
• Experience with cloud consoles, dashboards, or other high-complexity web applications
• Ability to communicate effectively with engineers using HTML, CSS, and JavaScript terminology

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.

The role 

Nebius Token Factory is a next-generation platform for LLM inference and deployment. It gives companies and developers access to dozens of state-of-the-art open-source models (LLMs, Vision, Embeddings, Image Generation) with enterprise-grade guarantees, including private endpoints, zero-retention data flow, transparent pricing, and easy scaling without GPU ops overhead.

Token Factory is part of Nebius, a company building next-generation cloud infrastructure for the global AI economy, helping teams solve real-world problems and scale AI without massive infrastructure costs or large in-house ML teams.

We are looking for a strong Product Designer  who will help turn complex AI infrastructure into a clear, controllable, and thoughtfully designed product for a professional audience. In this role, you’ll work on one of the most technically advanced AI products on the market, immerse yourself in modern LLM and AI infrastructure operating at production scale, and have real influence on UX and product decisions across core user scenarios.

You’re welcome to work in our offices in Amsterdam, Berlin, London or Prague with a hybrid work schedule.

Your responsibilities will include: 

• Designing clear, scalable interfaces for core end-to-end AI workflows: model selection and comparison, deployment and inference, inference observability and analysis, fine-tuning, dataset management, batch inference, and agent configuration.
• Own the end-to-end design of services and features within the Nebius Token Factory, from discovery to delivery.
• Being ready to write high-quality interface copy — clear, precise text that helps users navigate complex scenarios and make informed decisions.
• Developing a deep understanding of how AI systems work under the hood, translating complex technical processes (fine-tuning, data pipelines, agent workflows) into clear and manageable user interfaces.
• Collaborating with product managers to formulate hypotheses, validate them with data and user feedback, and improve key product scenarios.
• Using modern AI tools as part of the design process across research, ideation, and prototyping stages (Figma Make, Cursor, lovable.dev, ChatGPT, Claude, etc.).
• Working closely with product, engineering, and ML teams — discussing, revisiting, and improving solutions based on feedback and shared understanding.
• Clearly present design solutions and rationale to cross-functional teams
• Contribute to the development and maintenance of the design system, ensuring consistency and quality across the product  

We expect you to have: 

• 5+ years of experience in product teams (SaaS / B2B / DevTools experience is a strong plus). Strong product thinking and the ability to turn complex processes into clear and transparent user journeys.
• Experience working on technically complex products where understanding system logic and processes matters as much as UI. Ability to balance usability, consistency, and innovation in complex systems.
• Willingness to dive into the AI domain: how datasets are prepared for fine-tuning, how fine-tuning works, how agents and their workflows are structured.
• Openness to collaboration: ability to listen, argue constructively, and incorporate team feedback.
• Interest in UX research and a clear understanding of its value for product decisions.

It will be an added bonus if you have: 

• Experience with AI products, ML platforms, or developer tools.
• Understanding of API-first products.
• Experience designing enterprise-grade interfaces.
• Interest in product architecture and how systems work “under the hood.”

The Role

Your responsibilities will include:

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

We expect you to have:

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

It will be an added bonus if you have:

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

We conduct coding interviews as part of the process.

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

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

The role

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

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

What we do:

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

In this position, your responsibility will be to:

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

We expect you to have:

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

It would be an added bonus if you had:

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

We conduct coding interviews as part of the process.

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

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

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

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

The Product

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

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

The Role

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

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

In this position, your responsibility will be to

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

You may be a good fit if you:

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

Strong candidates may also have experience with:

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

We conduct coding interviews as part of the process.

The Product

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

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

The Role

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

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

In this position, your responsibility will be to

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

You may be a good fit if you:

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

Strong candidates may also have experience with:

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

We conduct coding interviews as part of the process.

The role

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

Your responsibilities will include:

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

We expect you to have: 

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

Nice to have:

Experience designing high-load and scaling services.

We conduct coding interviews as part of the process.

The role

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

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

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

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

What’s inside the platform

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

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

What you’ll do

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

In this role, you will:

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

Example projects

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

Tech stack

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

What we expect

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

Nice to have

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

We conduct coding interviews as part of the process.

The role

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

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

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

We conduct coding interviews as part of the process.

The role

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

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

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

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

Your responsibilities will include: 

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

We expect you to have:

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

Nice to have:

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

The role

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

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

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

What we do:

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

In this position, your responsibility will be to:

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

We expect you to have:

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

It would be an added bonus if you had:

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

We conduct coding interviews as part of the process.

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

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

In this role you will

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

We expect you to have:

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

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

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

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

We conduct coding interviews as part of the process.

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

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

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

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

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

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

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

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

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

About Nebius

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

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

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

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

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

The role

As a Senior Technical Program Manager, you will own the end-to-end delivery of GPU clusters and other critical IT infrastructure components that power next-generation AI workloads. In this high-impact role, you’ll coordinate engineering, networking, construction, and operations teams to deliver GPU clusters and critical IT infrastructure at hyperscale. You’ll work closely with infrastructure leadership to define strategy, manage risk, and ensure on-time, high-quality launches.You’ll play a key role in scaling our global infrastructure footprint across the EU markets.

Travel: This position may require on-site presence at data centers during key deployment phases.

Your responsibilities will include: 

• Lead end-to-end delivery of new data center programs, from design through handover to operations.
• Define and manage scope, schedule, and risks, maintaining focus on critical paths and proactive issue resolution.
• Translate business and technical requirements into actionable project plans and measurable deliverables.
• Oversee vendor and contractor execution, ensuring quality, budget, and schedule.
• Provide structured program reporting, including dashboards, documentation, and executive updates.

We expect you to have: 

• 7+ years of experience in technical program or project management, with direct involvement in large-scale IT infrastructure deployments.
• Solid technical background in relevant domains, with the ability to engage deeply in technical discussions and challenge solutions where needed.
• Proven ability to stay focused on critical paths and drive results in fast-paced, changing environments.
• Communication and stakeholder management skills; able to translate complex topics clearly.
• Leadership by influence and example in cross-functional or matrixed teams.
• Proficient with modern project management tools and methodologies (e.g., Jira, Asana, hybrid Agile/Waterfall).

It will be an added bonus if you have: 

• Understanding of construction projects structure and key risk factors in facility build-outs.
• Knowledge of HPC
• Experience in business processes design or automation tools development.
• PMP, PRINCE2, or similar industry certifications.

The role

As a Senior Technical Program Manager, you will own the end-to-end delivery of GPU clusters and other critical IT infrastructure components that power next-generation AI workloads. In this high-impact role, you’ll coordinate engineering, networking, construction, and operations teams to deliver GPU clusters and critical IT infrastructure at hyperscale. You’ll work closely with infrastructure leadership to define strategy, manage risk, and ensure on-time, high-quality launches.You’ll play a key role in scaling our global infrastructure footprint across the EU markets.

Travel: This position may require on-site presence at data centers during key deployment phases.

Your responsibilities will include: 

• Lead end-to-end delivery of new data center programs, from design through handover to operations.
• Define and manage scope, schedule, and risks, maintaining focus on critical paths and proactive issue resolution.
• Translate business and technical requirements into actionable project plans and measurable deliverables.
• Oversee vendor and contractor execution, ensuring quality, budget, and schedule.
• Provide structured program reporting, including dashboards, documentation, and executive updates.

We expect you to have: 

• 7+ years of experience in technical program or project management, with direct involvement in large-scale IT infrastructure deployments.
• Solid technical background in relevant domains, with the ability to engage deeply in technical discussions and challenge solutions where needed.
• Proven ability to stay focused on critical paths and drive results in fast-paced, changing environments.
• Communication and stakeholder management skills; able to translate complex topics clearly.
• Leadership by influence and example in cross-functional or matrixed teams.
• Proficient with modern project management tools and methodologies (e.g., Jira, Asana, hybrid Agile/Waterfall).

It will be an added bonus if you have: 

• Understanding of construction projects structure and key risk factors in facility build-outs.
• Knowledge of HPC
• Experience in business processes design or automation tools development.
• PMP, PRINCE2, or similar industry certifications.

The role

We are looking to hire a Senior Technical Project Manager to join our Dev Tools and Observability teams in Amsterdam or remote. Dev Tools team handle everything from the moment a developer starts writing code on their laptop to the moment the application is deployed in k8s or any other orchestrator. Observability Platform is a tool that unifies logs, metrics, traces, and many other services into a single ecosystem, which helps monitor the performance and health of applications. The impact on this position has high implications across various products.

The scope is - set up feedback loops from engineering teams, drive AI-related experiments, and help bring our planning and processes to a more mature level. This is a hands-on role: less reporting, more structuring, pushing things forward, and making results comparable.

Requirements:

• 5+ years as a TPM on cross-team initiatives or as an engineering manager/director. A few years as SWE is a plus.
• Strong technical background (architecture, infra, CI/CD, o11y basics).
• Excellent communicator, both spoken and written.
• Experience running cross-team work where no one has formal authority over everyone.
• Analytical approach to data and survey results.
• Experience with planning tools and willingness to adjust them.

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!

The role 

The Site Selection & Colocation Manager is responsible for identifying, evaluating, and securing optimal locations for new data center developments and colocation expansions. This role combines real estate strategy, technical due diligence, market analysis, and vendor management to support the company’s global data center growth. The manager will collaborate closely with engineering, construction, finance, legal, and network planning teams to ensure that selected sites meet operational, technical, and business requirements.

You’re welcome to work in our office in Amsterdam or Remote - United States.

Your responsibilities will include: 

• Lead the end-to-end site selection process for new data center facilities.
• Conduct market assessments, including power availability, fiber connectivity, land suitability, regulatory requirements, and risk factors.
• Build and maintain market intelligence on emerging data center regions, supply trends, energy markets, and colocation pricing.
• Evaluate and shortlist candidate sites through comparative analysis, scoring models, and feasibility studies.

• Coordinate environmental, geotechnical, hydrological, and seismic assessments.
• Assess infrastructure availability (power, water, fiber) and future scalability.
• Evaluate construction constraints, climate conditions, logistics access, and permitting feasibility.
• Work with engineering teams to ensure sites meet mechanical, electrical, and network resilience requirements.

• Identify colocation providers and evaluate facilities based on technical specifications, SLA requirements, and cost structure.
• Lead RFPs, negotiations, and contract execution with colocation and connectivity partners.
• Manage colocation lifecycle: renewals, expansions, migrations, and optimization of space/power allocations.
• Monitor vendor performance against SLA, uptime, compliance, and efficiency metrics.

• Work with data center design and construction teams to validate site feasibility and development timelines.
• Partner with legal on contract terms, property acquisition, lease terms, and regulatory compliance.
• Support finance with CapEx/OpEx modeling, ROI calculations, and business case development.
• Coordinate with public authorities, utilities, and permitting agencies as needed.

• Evaluate risks related to natural hazards, geopolitical risk, security, environmental constraints, and utility reliability.
• Ensure compliance with local regulations, zoning laws, and corporate standards.
• Maintain documentation for audits, reporting, and internal approvals.

We expect you to have: 

• Bachelor’s degree in Real Estate, Engineering, Business, Geography, or related field.
• 5–8+ years of experience in site selection, real estate development, colocation management, or data center infrastructure.
• Strong understanding of data center power, cooling, and network requirements.
• Experience in evaluating colocation providers and negotiating leases/SLAs.
• Analytical skills in market research, cost modeling, and risk assessment.
• Ability to manage multiple simultaneous projects across regions.
• Excellent communication, negotiation, and stakeholder management skills.

It will be an added bonus if you have: 

• Experience with hyperscale or large-scale data center development.
• Knowledge of utility procurement (power, water), renewable energy markets, and substation planning.
• Familiarity with geospatial tools (GIS), risk modeling, or data center capacity planning.
• Understanding of permitting processes and environmental regulations.

Summary:

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

The role

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

We expect you to have:

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

What we offer:

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

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

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

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

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

In this position, you will be responsible to:

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

Examples of outcomes you could drive as a Team Lead

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

What you will bring to the table:

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

It would be an added bonus if you had:

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

The Role

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

Your responsibilities will include:

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

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

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

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

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

We expect you to have:

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

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

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

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

It will be an added bonus if you have:

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

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

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

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

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

We are seeking a Staff or Principal Applied AI Researcher to join a fast growing team building an agent native search platform - the web access layer for AI systems.

You can think of this as Google for AI agents: a system designed for machines, not humans. We are building agentic search, where AI systems actively plan, retrieve, evaluate, and refine information rather than simply returning results. As AI becomes the primary interface to the web, this layer will replace the role of traditional search engines.

We are designing how AI agents - not humans - retrieve, evaluate, and reason over web data in real time, under strict latency and reliability constraints. This means solving retrieval and ranking under entirely new access patterns and at significant scale, with systems operating over constantly changing, unstructured data and serving tens of thousands of production workloads 24 by 7.

This role comes with ownership over key parts of our applied AI research direction and system design, with a strong expectation of defining new approaches and shipping measurable impact in production.

What you'll work on:

• Designing agent native retrieval systems optimised for machine consumption rather than human search UX
• Building systems where LLMs iteratively plan, query, refine, and reason over results
• Developing ranking and retrieval approaches for multi step, agent driven workflows under real world constraints

Your responsibilites:

• Drive applied research and technical direction across retrieval and ranking systems
• Design and evolve multi stage retrieval architectures (query understanding, rewriting, reranking, iterative retrieval)
• Develop methods for grounding LLMs in real time web data at scale
• Define and implement new evaluation paradigms and metrics for agentic systems, where correctness is not reducible to clicks
• Lead experimentation on modern retrieval approaches (embeddings, hybrid search, reranking) and bring them into production
• Analyse trade-offs across relevance, latency, and cost at scale
• Work closely with engineering to deploy systems in high throughput, low latency environments
• Own ambiguous problems end to end and contribute to product and research direction
• Mentor engineers and help raise the technical bar of the team

Must haves:

• 8+ years of experience in applied AI, ML, or software engineering
• Proven track record of shipping ML or AI systems to production at scale
• Deep experience with search, retrieval, ranking, recommendation systems, or assistants
• Strong understanding of modern deep learning, especially transformers and embeddings
• Experience with LLM integrated or knowledge intensive systems
• Experience designing evaluation frameworks and metrics for ML systems
• Strong programming skills in Python and at least one of Go, C++, or similar
• Ability to operate in a fast moving, product driven environment with high ownership and autonomy

Nice to haves

• Experience with large scale search or recommendation systems
• Background in agentic AI systems (agents, tool use, autonomous workflows)
• Experience with RAG, multi step retrieval, or tool use
• Publications, open source, or similar signals of technical depth and impact

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

The Team Assistant – Corporate Development will provide high-quality administrative and coordination support to the Corporate Development team. This role is critical to ensuring the team operates efficiently in a dynamic, fast-paced environment by managing scheduling, travel, meeting logistics, documentation, and day-to-day coordination across stakeholders.

The role contributes to the effectiveness of the Corporate Development function by enabling smooth team operations, supporting internal and external interactions, and ensuring strong organization across multiple priorities. The Team Assistant will work closely with senior stakeholders and cross-functional partners to help the team stay focused, well-prepared, and operationally effective.

Your responsibilities will include:

We expect you to have:

• 3–7 years of experience in a Team Assistant, Executive Assistant, or similar support role.
• Experience supporting senior stakeholders and working with complex, fast-changing schedules.
• Strong organizational and prioritization skills, with close attention to detail.
• Ability to manage multiple tasks simultaneously and work effectively under pressure.
• Strong written and verbal communication skills.
• Professional, reliable, and discreet approach to handling sensitive information.
• Proficiency in standard office tools such as Google Workspace and/or Microsoft Office.
• Experience coordinating meetings, travel, documentation, and administrative processes in a structured way.

Nice to have:

• Experience in a high-growth, fast-paced, or international environment.
• Background supporting teams in tech, consulting, finance, investment, legal, or other dynamic business functions.
• Experience working with senior leadership or executive-level stakeholders.
• Comfort working across multiple functions and coordinating with different teams.
• Experience supporting project, transaction, or deal-related administrative processes.

The role

Nebius is looking for a Technical Product Manager – Networks to join the team. In this role, you will will own the vision, roadmap, and priorities for networking services, including overlay (VPC) networks, underlay networks (data center fabric and WAN), and DNS.

Also, you will be responsible for shaping and managing backlogs for networking service teams and leading key, company-wide initiatives related to connectivity. This role requires strong technical depth combined with the ability to coordinate across engineering, development, product, technical support and go-to-market teams.

Your responsibilities will include: 

• Own and manage the product backlog for network service teams
• Lead and coordinate key cross-company implementations involving networking and connectivity
• Work closely with engineering and architecture teams to define product requirements and deliver new networking features
• Partner with product marketing and technical pre-sales/post-sales teams on technical publications, go-to-market activities, customer engagement, acquisition, and retention activities related to networking features
• Ensure the delivery of networking services that meet high standards for performance, security, scalability, and reliability.

We expect you to have: 

• Experience designing, implementing, or operating large-scale automated network solutions in senior engineering, architecture, or technical leadership roles (e.g., large enterprises, hyperscalers, cloud providers, or other advanced technology companies)
• Hands-on familiarity with technologies such as OVS, DNS, L2VPN, L3VPN, VXLAN, BGP, and IPv6 at scale
• Strong technical expertise in at least two of the following areas:
  • Linux networking stack
  • Overlay / SDN networking
  • ISP or large-scale service provider networking
  • DevNet / network automation
• Proven track record of delivering complex technical initiatives requiring coordination across multiple teams or stakeholders
• Technical leadership experience is a strong plus
• Product management experience is not required, but a strong willingness to learn and grow into the role is essential.

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. 

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. 

The role

As a Technical Project Manager, you will own the delivery of a defined workstream within large-scale data center and GPU infrastructure programs. In this role you’ll be responsible for tracking progress, managing dependencies, and ensuring your workstream is delivered on time and at quality.
This is a hands-on role at the intersection of infrastructure, execution, and coordination, with strong exposure to real-world data center delivery.
Travel: On-site presence at data centers will be required during key deployment phases.

Your responsibilities will include:

• Own delivery of a defined workstream within a larger data center or infrastructure program.
• Track scope, schedule, and dependencies, escalating risks when needed.
• Coordinate with engineering, networking, construction, and operations teams.
• Maintain clear and structured reporting on progress, risks, and blockers.
• Support vendor and contractor coordination within your scope.
• Work closely with the Senior TPM to align on priorities and execution approach.

Technical Scope & Expectations

This role requires exposure to physical infrastructure environments, not only software-based projects.
You should be comfortable working with or learning about:

• Data center environments: basic understanding of infrastructure readiness (power, cooling, space, networking dependencies).
• Compute infrastructure: knowledge about server and storage equipment.
• Networking: cabling, connectivity, and integration dependencies.
• Deployment & bring-up: understanding how systems move from installation to operational readiness.

You are not expected to be an expert, but you should:

• Be willing to learn technical concepts quickly.
• Understand how different parts of infrastructure depend on each other.
• Identify when something is not ready or at risk and escalate appropriately.
• Communicate effectively with technical teams.

We expect you to have:

• 2–5 years of experience in project management, operations, or technical coordination roles.
• Ability to organize work, track progress, and manage multiple tasks simultaneously.
• communication skills and ability to work with cross-functional teams.
• Structured thinking and attention to details.
• Willingness to learn and grow in a fast-paced, technical environment.

It will be an added bonus if you have

• Exposure to data center, networking, or hardware-related projects,
• Familiarity with project management tools (Jira, Asana, etc.),
• Understanding of cloud environments infrastructure,
• Certifications or coursework in project management.

New data center development:

We give you the opportunity to work with cutting-edge technologies in data operations, cloud computing and infrastructure management. As global data center operations grow, there will be ample opportunities for career progression. Working in the data center directly impacts performance, customer satisfaction and efficiency, with the opportunity to contribute to new data center projects.You’ll collaborate with experts in AI data center development and operations, gaining insights from leaders in the field. This environment fosters innovation, and allows you to work on solutions that exceed industry standards in design and deployment.

The role

• Lead large cross-team IaaS projects from planning to delivery.
• Break down project scope into phases, milestones, dependencies, and tasks.
• Coordinate execution across multiple technical teams and keep everyone aligned.
• Build and maintain project plans, document decisions, architecture context, and artifacts.
• Run regular project syncs, track progress, identify blockers early, and drive mitigation.
• Own timeline tracking and delivery forecasting; proactively highlight risks and trade-offs.
• Support product managers with execution orchestration across several engineering teams.
• Improve delivery transparency: status reporting, milestone, and clear next steps for stakeholders.

• Solid understanding of public cloud fundamentals and core IaaS principles.
• Good technical awareness of cloud building blocks, including: virtualization (KVM/QEMU), Kubernetes, VPC, storage, API.
• Strong project decomposition and execution management skills in technical environments.
• Ability to run structured cross-functional ceremonies and keep technical teams synchronized.
• Strong communication skills: concise status updates, risk communication, and stakeholder alignment.

• Experience in cloud infrastructure, AI/GPU platforms, or distributed systems projects.
• Experience working with both product and engineering stakeholders in platform teams.
• Familiarity with release planning and dependency/risk management across multiple streams.

• Projects are delivered with clear stage gates, realistic timelines, and predictable execution.
• Cross-team dependencies are visible early and resolved before they become blockers.
• Product and engineering have a shared view of scope, progress, and delivery risks.