Role

We are looking for a Product Manager — Public Notifications & Communications to take our customer-facing notification experience to the next level. Nebius already has a working notification infrastructure — multi-channel delivery (email, Slack, in-console) and integrations across the platform. The next step is turning this foundation into a product: richer message content, self-serve access for all product teams, proactive system health signals, and communication quality that sets Nebius apart from hyperscalers.

What you will do

• Own the product vision and roadmap for the Notifier platform — expanding from core delivery infrastructure to a self-serve notification system usable by all Nebius products.
• Define and evolve notification standards: content guidelines, severity taxonomy, actionability requirements, and delivery SLAs across all channels.
• Improve maintenance communication: sharpen pre-notification processes, message quality, and multi-product coordination.
• Identify opportunities to reduce notification noise at scale and introduce missing event types that customers would find genuinely valuable.
• Work with platform teams to introduce proactive system health alerts — giving customers visibility into cluster state before issues escalate.
• Track and report notification quality metrics: delivery rates, customer feedback, and satisfaction trends.

What we expect

• Strong product opinion on when a notification adds value versus creates noise.
• Familiarity with cloud operational communication patterns: maintenance windows, service status, system health alerts.
• Technical understanding of notification delivery systems: queues, retry logic, multi-channel routing.
• Ability to set and evolve quality standards — including defining content policies and message templates.

Nice to have

• Experience with cloud infrastructure platforms (IaaS, PaaS) and their operational communication patterns.
• Familiarity with reliability concepts: SLOs, error budgets, maintenance windows.
• Experience driving cross-team product initiatives — aligning multiple engineering teams around shared requirements and delivery.

Success in this role

• All Nebius product teams can self-serve new notification types without cross-team coordination overhead.
• Notification content is consistently specific, actionable, and relevant — customers see notifications as a useful signal, not noise.
• Maintenance communication is timely and consistent across all products and regions.
• Customers have proactive visibility into cluster health before issues affect their workloads.

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

Nebius is looking for an experienced, community-focused professional to join our global startup team as Startup Community Manager - France. In this role, you’ll take ownership of developing and executing our startup community engagement strategy across key markets, cultivating relationships with developer communities, accelerators, universities, and founder networks.

You’ll focus on delivering high-impact events, meaningful engagement programs, and tailored resources that activate and grow Nebius’ presence within the global AI startup ecosystem. You’ll work cross-functionally to ensure seamless execution and measurable results, helping position Nebius as the cloud partner of choice for AI-native startups worldwide.

You are welcome to work remotely from Paris.

Your responsibilities will include:

Develop and Manage Ecosystem Partnerships

• Identify, build, and maintain strategic relationships with key accelerators, universities, developer communities, research organisations, and other startup ecosystem partners globally.
• Act as a trusted Nebius representative within the global startup ecosystem, strengthening our visibility and adoption among founders, developers, and technical teams.

Design and Deliver Startup Engagement Programs

• Create and execute scalable, community-driven initiatives that attract, support, and retain high-growth AI startups.
• Ensure Nebius’ offerings deliver real value to founders and technical teams through tailored resources, onboarding support, and ongoing enablement.

Lead High-Impact Events and Ecosystem Activations

• Plan and execute founder meetups, technical workshops, hackathons, and summits that showcase Nebius’ commitment to supporting the AI startup community.
• Collaborate with partners and internal teams to maximise event impact, drive attendance, and amplify engagement across priority markets.

Drive and Nurture Startup Pipeline

• Work cross-functionally with sales and marketing teams to identify, engage, and convert high-potential startups into long-term Nebius users.
• Maintain clear tracking of engagement activities, pipeline development, and program participation across regions.

Enablement and Community Resources

• Develop and maintain best-practice playbooks, onboarding guides, case studies, and enablement materials to educate startups and partners on effective use of Nebius’ platform.
• Ensure consistent, high-quality resources that support startup adoption and success.

Measure and Optimise Community Success

• Own and deliver against clear key performance indicators (KPIs) such as lead generation, community growth, event outcomes, and pipeline contribution.
• Maintain a strong results-driven mindset, ensuring all programs and initiatives are aligned to measurable goals.
• Use data and feedback proactively to evaluate impact, identify opportunities, and optimise strategies for continuous improvement.

Collaborate Across Teams

• Partner closely with internal stakeholders—including marketing, sales, product, and solutions architecture—to ensure community insights inform broader go-to-market strategies and product development.
• Champion the voice of the startup and developer community within Nebius.

We expect you to have:

• Minimum of 3 - 5 + years of professional experience in community management, partnerships, or ecosystem development, with at least 1.5 years working in the startup ecosystem (e.g., accelerators, AI/cloud startups, developer or founder communities).
• Proven ability to build and manage partnerships within the global AI and startup ecosystem.
• Experience developing and executing high-impact community programs, events, or partner initiatives.
• Strong understanding of the AI/startups landscape, including developer and founder needs.
• Excellent organisational, communication, and presentation skills, with experience influencing partners and internal stakeholders.
• Ability to work independently and collaboratively in a fast-paced, high-growth, cross-functional environment.
• Familiarity with AI infrastructure, cloud computing, or developer tools, with the ability to learn new technologies quickly.
• Genuine passion for AI, cloud computing, and supporting startup founders.

It will be an added bonus if you have:

• Established network in the global AI and startup ecosystem, with existing relationships across mainstream accelerators, investors, developer communities, and founder networks.
• Hands-on experience planning and delivering events ranging from meetups and workshops to hackathons and summits.
• Experience in technology partnerships, developer advocacy, or customer enablement for cloud or AI/ML solutions.
• Proven track record of driving results through community engagement and partner collaboration.

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.

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

The OFCI Equipment Procurement Manager – Data Centers is responsible for the technical and commercial procurement of Owner-Furnished, Contractor-Installed (OFCI) equipment for mission-critical data center facilities. The role ensures that long-lead, high-reliability power and cooling equipment meets stringent performance, redundancy, and availability requirements while aligning procurement schedules with construction, commissioning, and go-live milestones.

This position reports to the Procurement Manager EU Team Lead and is a remote position serving the geographically distributed projects for the company. 

Your responsibilities will include: 

Technical Scope & Engineering Coordination

• Define OFCI equipment scope in collaboration with data center design, engineering, and construction teams
• Review and validate technical specifications, single-line diagrams, layouts, and equipment datasheets with data center design, engineering, and construction teams
• Ensure compliance with data center design criteria (Tier levels, redundancy, fault tolerance, uptime targets)
• Manage technical clarifications, deviations, and vendor compliance matrices

Vendor Selection & Technical Procurement

• Issue RFQs/RFPs for critical data center infrastructure equipment
• Lead technical and commercial bid evaluations with engineering stakeholders
• Conduct vendor technical interviews and design alignment workshops
• Negotiate contracts covering performance guarantees, availability, FAT requirements, delivery milestones, and warranties

Critical Equipment Oversight

• Manage procurement and delivery of long-lead, mission-critical equipment, including:
• Electrical: generators, medium- and low-voltage switchgear, transformers, UPS systems, PDUs, busways
• Mechanical: chillers, cooling towers, CRAH/CRAC units, pumps, heat exchangers
• Controls & Monitoring: BMS, EPMS, SCADA, protection and control systems

Manufacturing, FAT & Quality Control

• Monitor vendor engineering, manufacturing, and testing schedules
• Review vendor drawings, protection studies, and control logic
• Coordinate and participate in FATs, integrated systems testing (where applicable), and inspections
• Manage non-conformances, corrective actions, and technical change control

Logistics, Site Delivery & Installation Readiness

• Develop logistics strategies for oversized and critical equipment
• Coordinate international shipping, customs clearance, and just-in-time delivery
• Ensure equipment preservation, storage, and environmental controls on site
• Support installation readiness reviews and contractor handover

Schedule, Risk & Interface Management

• Track long-lead items and procurement activities on the project critical path
• Identify and mitigate risks related to capacity, lead times, factory constraints, and supply chain disruptions
• Coordinate interfaces between OFCI equipment and contractor-installed systems
• Provide detailed procurement and risk reporting to project leadership

Documentation, Commissioning & Handover

• • Ensure completeness and accuracy of as-built documentation, O&M manuals, and warranties
  • Support commissioning, IST, and turnover to operations teams
  • Close out OFCI packages in accordance with data center operational requirements

We expect you to have: 

• Bachelor's degree in a relevant field of study, (i.e. Construction Management, Engineering, Business, Supply Chain Management, Project Management, etc.) or equivalent combination of experience and technical training.

• 5+ years of experience in technical procurement or engineering for data centers or mission-critical facilities
• Proven experience procuring long-lead, high-reliability OFCI equipment
• Strong understanding of critical power and cooling systems
• Experience with FATs, commissioning, and contractor coordination

It will be an added bonus if you have: 

• Hyperscale or colocation data center experience
• Knowledge of Uptime Institute Tier standards or equivalent reliability frameworks
• Familiarity with IEC, IEEE, NFPA, NEC, ASHRAE, and local codes 

• 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.

• 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 team

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

The role

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

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

Your responsibilities will include: 

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

We expect you to have: 

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

It will be an added bonus if you have: 

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

Customer experience

Customer experience at Nebius AI Cloud involves tackling customers’ challenges and directly impacting their success by solving real-world AI and ML problems at massive GPU cloud scale. You’ll not only resolve issues, but play a key role in shaping clients’ business success by optimizing their AI solutions.

Working with advanced GPUs such as H200, B200 and GB200, as well as modern ML frameworks, you’ll influence the development of the Nebius AI Cloud and gain experience at the intersection of infrastructure and AI. With minimal bureaucracy, you’ll have the freedom to innovate, take ownership and drive change. Opportunities for growth are abundant in this vibrant and supportive professional community.

The role

We are looking for a Partner Solutions Architect to serve as the technical interface between Nebius and our strategic technology partners, ranging from data platforms and MLOps vendors to AI frameworks and ISVs that build on GPU infrastructure. 

This is a hands-on engineering and integration role. You will design and develop integrated solutions, build reference implementations, enable partner engineering teams, and ensure joint customers succeed with combined offerings. You will influence Nebius’ product roadmap and drive deep technical collaboration across partner ecosystems.

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

Your responsibilities will include: 

• Own the technical relationship with strategic partners as the primary interface to Nebius engineering and product
• Design and architect high-impact integration solutions, delivering clear joint customer value
• Build and maintain reference implementations and production-grade integrations
• Define enterprise-ready integration patterns (networking, security, compliance, observability)
• Translate partner and customer feedback into actionable product and roadmap requirements
• Enable partner teams through technical documentation, training, and demo environments
• Provide technical leadership in joint customer deployments, architecture reviews, and complex troubleshooting

We expect you to have: 

• 5+ years in solutions architecture, partner engineering, or technical pre-sales at cloud or data platform companies
• Strong expertise in cloud infrastructure
• Hands-on experience with GPU-accelerated AI/ML workflows (training, inference, MLOps)
• Proven background in integration architecture (API design, data pipelines, security, observability)
• Experience with Python and IaC tools
• Excellent communication skills with the ability to engage technical and non-technical stakeholders

It will be an added bonus if you have: 

• Track record of building or scaling partner technical programs or ecosystems
• Experience working with or at Snowflake, Databricks, AWS, Azure, or GCP
• Background in ML lifecycle (training pipelines, fine-tuning, inference optimization, RAG

• Write and maintain UI copy in Nebius Console that improves and streamlines the user experience, ensuring consistency and alignment with product documentation.
• Provide alternative UI copy options based on the proposed design solutions.
• Collaborate closely with product managers, designers, and engineers on product initiatives.
• Develop and maintain voice & tone guidelines; define and scale content patterns within the design system.
• Simplify complex technical scenarios into clear, actionable interface language.
• Conduct content audits of the existing interfaces and identify areas for improvement.
• Actively participate in the life and processes of the Product Design Team.

• 5+ years of experience in UX writing / content design.
• Strong product thinking and the ability to approach design as a system of interconnected user scenarios.
• Excellent written and spoken English.
• Familiarity with cloud computing concepts (virtual machines, containers, Kubernetes, storage, networking, etc.) and ML/AI concepts (training, inference, fine-tuning, etc.).
• Proficiency in Figma.
• A portfolio featuring real interface cases (before/after examples and clear explanation of decision logic).
• Solid understanding of core UX principles: user flows, edge cases, states, and system feedback.

• Experience in technical writing.
• Experience using AI-powered plugins in Figma or other tools to support content creation workflows.
• Review UI texts directly in the codebase and occasionally update or fix copy within the code when necessary.

The role

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

Your responsibilities will include: 

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

We expect you to have: 

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

It will be an added bonus if you have: 

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

The role

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

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.

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.

• 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!

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

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

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.

About the role:

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

Responsibilities:

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

• Improve performance of inference engines GPU platforms 

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

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

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

Required Qualifications:

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

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

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

• Solid understanding of CPU/GPU architecture and memory hierarchy 

Preferred Qualifications: 

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

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

• Knowledge of Linux internals, drivers, or compiler toolchains 

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

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

We conduct coding interviews as part of the process.

The role

We seek an experienced Senior ML Solutions Architect to support customers leveraging Nebius Token Factory's serverless inference platform for open-source LLMs across multiple modalities. In this role, you will be collaborating with clients to design and implement customized LLM-based solution and architect scalable AI applications using our served models, and working together with our backend team to improve our platform to match the clients' needs.

You’re welcome to work remotely from Europe.

Your responsibilities will include: 

• Design and implement LLM-based solutions using Nebius Token Factory’s inference services to drive business value and support customer goals
• Build production-ready applications leveraging our serverless LLM APIs, including multimodal models (text, vision, audio) and domain-specific models
• Provide technical expertise in prompt engineering, RAG architectures, model selection, and inference optimization
• Collaborate with product and engineering teams to surface customer feedback and shape the platform roadmap
• Guide customers in scaling from POC to production with a focus on performance, reliability, and cost efficiency

We expect you to have: 

• 5+ years of experience in ML/AI systems, with at least 2 years focused on LLMs and generative AI
• Deep knowledge of the LLM ecosystem, including model architectures and fine-tuning approaches
• Hands-on experience with:
  • Prompt engineering and LLM pipeline development, including evaluation
  • Agentic frameworks such as Langchain, Langsmith, smolagents, or equivalent
  • Vector databases and RAG implementation patterns
  • Deploying LLM-powered applications using APIs from OpenAI, Anthropic, or open-source models
• Strong Python programming skills
• Excellent communication skills, with the ability to clearly explain technical concepts to diverse audiences

It would be an added bonus if you have: 

• Experience with inference frameworks and libraries (e.g., vLLM, SGLang, TensorRT-LLM, Transformers)
• Familiarity with inference optimization techniques such as quantization, batching, caching, and routing
• Work with multimodal AI models (e.g., vision-language, speech)
• Proficiency with DevOps tools (Docker, Kubernetes)
• Contributions to open-source ML/AI projects

Preferred technical stack:

• Programming Languages – Python
• ML Frameworks and Libraries – vLLM, SGLang, TensorRT-LLM, Transformers, OpenAI/Anthropic SDKs
• Frameworks for Agentic Pipelines – Langchain / Langsmith / smolagents / equivalent
• API and Web Frameworks – FastAPI, Flask
• MLOps and DevOps tools – Kubernetes (K8s), Docker, Git
• Cloud Platforms – AWS (SageMaker, Bedrock), GCP (Vertex AI), Azure (Azure ML)

The role

We’re looking for a Security Product Manager to join our team. Security Product Manager is responsible for conveying the company’s security strengths to customers, partners and the market at large. This includes participating in relevant security partnership initiatives, influencing security positioning and branding, and working closely with internal teams to ensure company’s security posture and security products is communicated effectively to all stakeholders. By combining expertise in compliance requirements with a customer-centric approach, Security Product Manager helps position security as a competitive advantage rather than just an internal obligation. 

Your responsibilities will include: 

1. Product Management 

• Define the vision and roadmap for Nebius’ security products. 
• Owning the ideation, postmortem, prioritization, backlog, and customer feedback processes. 
• Guiding new features, systems and services from inception to launch, while keeping customers at the center of everything. 

2. Customer-facing communications 

• Lead public-facing communications around security updates or changes in compliance status. 
• In the event of a security incident, coordinate user messaging (email notifications, press releases, FAQs) with support from the Head of Security Products and CISO. 
• Gather user feedback on user experience and security to guide continuous improvements. 

 3. Competitive analysis and market research 

• Conduct ongoing research on industry benchmarks, emerging security standards and technologies, and competitor certifications. 
• Identify gaps and opportunities in organization’s product security posture; propose strategic initiatives that differentiate the company’s security story in the market. 
• Stay informed about new regulations or frameworks that may influence future product certifications or transparency requirements (e.g., privacy laws, data sovereignty standards). 

 4. Certification and audit support, service ownership 

• Collaborate with the CISO office to gather technical evidence or make necessary product enhancements that satisfy certification requirements. 
• Take ownership of some security-related services of Cloud platform. 
• Track and maintain a certification roadmap (ISO 27001, SOC 2, HIPPA, etc.), working closely with CISO, GRC & Compliance, Corporate Security departments. Communicate timelines, goals and status updates to leadership and sales representatives. 

5. Cross-functional collaboration 

• Coordinate with multiple Product Managers to align security goals with other product roadmaps, ensuring a consistent narrative between product security and external messaging. 
• Work with Platform Security, GRC & Corporate Security and legal teams to gather essential information for security products enhancements (e.g., penetration test summaries, compliance reports). 
• Work with Customer-facing teams to address client inquiries about security posture and guide them on using security features optimally. 

We expect you to have: 

• 3+ years of Product Management or Program Management experience with a focus on security initiatives. 
• Basic knowledge of compliance frameworks (e.g., SOC 2, ISO 27001, GDPR) and familiarity with how they translate into business value. 
• Proven ability to communicate technical concepts in a clear, customer-friendly manner (e.g., writing content, speaking at webinars or conferences). 
• Stakeholder management skills to align with other Product Managers, CISO staff, engineering, marketing, and customer-facing teams. 
• Analytical mindset: comfortable defining success metrics (e.g., security feature adoption, NPS around trust, certification progress) and making data-driven decisions. 
• Project management skills: demonstrated ability to manage inter-team collaboration within company-wide projects, ensuring timely delivery of cross-functional tasks and alignment with compliance goals. 

It will be an added bonus if you have: 

•  Certifications such as CISSP, CISM, or PMP; prior experience in regulated industries; prior experience working for Cloud Service Provider.

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:

We are hiring a Senior Technical Project Manager for the External Solutions Department, which includes Managed Service Platform, Managed Skypilot & Integrations, and Serverless & Marketplace services. These teams deliver external-facing cloud capabilities, integrations, and managed offerings used across the Nebius platform.

The scope: drive planning and execution across multiple engineering and product teams, align requirements from Sales, Partnerships, and other stakeholders, and help bring clarity and structure to how we launch new external services. This includes coordinating service releases, working with Legal, preparing deployments to new datacenters, and managing expectations and demand signals from various internal and external groups. The role is hands-on: less reporting, more driving alignment, structuring work, and pushing programs forward.

Requirements

• 5+ years as a TPM driving multi-team programs or as an engineering manager/director; SWE background is a plus. staff engineer/staff architect is plus.
• Strong technical foundation (cloud architecture, infra, APIs, CI/CD, service deployments).
• Experience launching services, managing cross-team work, and aligning stakeholders without formal authority.
• Ability to work with Sales, Partnerships, Legal, and Engineering to manage expectations and consolidate external demand.
• Analytical mindset, experience with planning tools, and ability to adapt processes as the organization grows.

The role

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

In this position, you will be responsible for:

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

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

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

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

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

We expect you to have:

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

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

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

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

It would be a plus if you have:

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

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

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

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

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

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

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

We offer competitive salaries ranging from $170k-$300k + equity based on your experience.

We conduct coding interviews as part of the process.

The role 

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

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

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

Your responsibilities will include: 

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

We expect you to have: 

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

It will be an added bonus if you have: 

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

The role 

We are seeking a Channel Partner Manger to lead engagement and growth with our most strategic partners in the Systems Integrator (SI), Managed Service Provider (MSP) and Value-Added Reseller (VAR) segments in the DACH and Nordics region. This senior-level role will work hand-in-hand with the Head of Channel and Head of the Region to develop and execute strategies that position Nebius as the partner of choice for these key segments.

The ideal candidate will bring extensive experience managing and scaling relationships with SIs, MSPs, and VARs, a strategic mindset and the ability to drive impactful partner enablement programs. This is a high-impact role, offering the opportunity to shape Nebius’ partner ecosystem and contribute to the company’s long-term growth.

You’re welcome to work remotely from the DACH or Nordics region.

Your responsibilities will include: 

• Strategic partner engagement: Build and deepen relationships with top SIs, MSPs and VARs, ensuring alignment with Nebius’ strategic goals and objectives
• Partner enablement: Design, develop and execute partner enablement programs that equip partners to successfully position and sell Nebius’ GPU IaaS solutions
• Collaboration with leadership: Work closely with Head of Channel and Head of the Region to align on strategic priorities, partner initiatives and business growth opportunities
• Contract negotiation and execution: Partner with team members to negotiate agreements, finalize contracts and ensure smooth implementation of sales enablement initiatives
• Business development: Identify new partnership opportunities within the SI, MSP and VAR segments, driving incremental revenue growth
• Sales alignment: Collaborate with sales teams to ensure seamless integration of partner activities into the broader sales strategy, tracking progress against key metrics
• Performance analysis: Monitor and analyze partner performance, providing actionable insights to refine programs and maximize impact
• Travel: up to 25% 

We expect you to have: 

• A minimum of 7-10 years of DACH and Nordics channel management experience, with a proven track record of working with enterprise-level partners in the SI, MSP, and VAR sectors. Experience working with enterprise customers to scale and drive adoption of cloud-based solutions is essential
• Strong, existing relationships with key SIs, ISVs, and MSPs who have a track record of serving enterprise customers. You should be able to leverage this network to accelerate the growth of Nebius' partner ecosystem
• Strong technical knowledge of cloud-based solutions, with experience enabling partners to sell complex products (preferably GPU IaaS or similar cloud infrastructure solutions) to enterprise customers
• Demonstrated experience in working with enterprise sales teams and marketing functions to co-create sales strategies, develop marketing materials, and execute joint initiatives that resonate with large-scale enterprise customers
• Ability to develop high-level strategic plans for enterprise channel growth while also diving into the tactical aspects of partner enablement, contract negotiations, and performance tracking
• Experience selling, enabling, and supporting enterprise solutions, particularly in cloud, IaaS, and GPU-based offerings. Comfort in understanding and articulating the technical value of solutions to both technical and business stakeholders within enterprise accounts
• Demonstrated success in driving revenue growth and scaling partner ecosystems in an enterprise context
• Ability to present Nebius effectively on presentations, with senior leadership, technical teams, and enterprise partners, ensuring clear and actionable messaging around Nebius’ offerings
• Fluent German and English are a must have

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 

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

In this position, your responsibility will be to:

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

We expect you to have:

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

Ways to stand out from the crowd:

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

The role

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

In this position, you will be responsible for:

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

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

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

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

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

We expect you to have:

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

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

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

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

It would be a plus if you have:

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

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

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

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

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

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

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

We conduct coding interviews as part of the process.

The role 

We are looking for a Senior Sales Strategy & Ops Specialist to join our GTM  Strategy & Operations team with a focus on supporting regional Sales leaders across planning, forecasting, and pipeline governance.

You will act as a strategic business partner to Sales leadership and support the execution of our EMEA go-to-market strategy through data-driven insights, process optimization, and operational excellence. 

This role will own key processes related to quarterly planning cycles, territory alignment, forecast accuracy, pipeline health, and CRM governance. You will ensure operational consistency across the region and provide visibility into performance metrics that drive revenue outcomes. 

We are looking for a proactive and detail-oriented professional who combines strong analytical skills with structured thinking and execution rigor. The ideal candidate is comfortable working with large datasets, building dashboards, improving sales processes, and collaborating cross-functionally with Finance, Marketing, and GTM stakeholders. 

You thrive in a fast-paced, high-growth environment, can manage multiple priorities simultaneously, and communicate effectively with stakeholders at different levels of the organization. 

You’re welcome to work remotely from the EMEA region.

Your responsibilities will include: 

• Support EMEA Sales leadership in weekly forecast reviews and pipeline inspections
• Maintain and improve forecast tracking models and reporting structures
• Build and maintain dashboards in CRM / BI tools to monitor bookings, pipeline generation, conversion rates, and attainment
• Ensure CRM data hygiene and enforce standardized pipeline management practices
• Support territory alignment updates and account ownership changes
• Assist in quarterly planning cycles (target tracking, headcount tracking, performance visibility)
• Partner with Finance on revenue visibility and reporting alignment
• Monitor lead routing logic and GTM workflows across HubSpot and Salesforce
• Identify process gaps and propose operational improvements
• Support documentation of GTM processes and internal playbooks
• Assist with system enhancements and new tool rollouts
• Provide ad-hoc analysis to support business decisions 

We expect you to have:

• 4-5+ years of experience in Sales Operations, Revenue Operations, Business Operations, Consulting, or a similar analytical function (preferably in SaaS or technology)
• Strong hands-on experience with CRM systems (Salesforce and/or HubSpot)
• Experience working with forecasting processes and pipeline reporting
• Proficiency in Excel/Google Sheets and SQL; experience working with large datasets
• Strong attention to detail and ability to manage multiple priorities
• Clear communication skills and ability to collaborate cross-functionally
• Comfortable working in a fast-paced, scaling environment 

About the Product 

Token Factory is focused on building a next-generation platform that enables companies to seamlessly integrate AI into their products and workflows. Our vision is to create a powerful, open, and scalable alternative for deploying and managing AI systems—making advanced AI infrastructure more accessible to both fast-growing startups and large enterprises. 

We work with a wide range of customers, from AI-first companies to established technology organisations, helping them run AI workloads reliably at scale. Our goal is to become a leading platform for high-performance AI inference, delivering predictable latency, strong reliability, and the ability to scale to meet demanding production needs. 

Customer feedback plays a central role in how we build—our development process is highly iterative and closely aligned with real-world use cases. 

 About the Team 

We are a fast-growing, distributed team of engineers and product professionals based primarily in Europe. The team brings together strong backend, frontend, product, and business expertise, with a shared focus on building impactful, scalable systems. 

While we initially started without deep specialisation in AI/ML, the team has rapidly grown into the  space—demonstrating strong ownership, curiosity, and the ability to tackle complex technical challenges. 

Technology & Environment 

Our work is deeply integrated with a broader cloud and infrastructure ecosystem. We primarily use Go and Python to build and scale backend systems and collaborate closely with teams focused on areas such as infrastructure, observability, billing, and AI research. 

The platform continues to evolve from a lightweight integration layer into a more comprehensive system, including custom infrastructure, optimisations, and deeper control over performance and reliability. 

What We’re Working On 

• Scaling distributed systems: Expanding our platform to handle significantly increased workloads while maintaining performance and reliability  

• Improving reliability: Enhancing system stability and uptime to meet enterprise-grade expectations  

• Optimising AI performance: Continuously adapting to new models, hardware, and runtime improvements  

• Expanding platform capabilities: Building beyond inference into broader AI infrastructure, including data pipelines, customization, and advanced usage features  

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.

Why It’s Interesting 

This is an opportunity to work at the intersection of distributed systems, cloud infrastructure, and applied AI, tackling real-world scalability challenges and shaping how companies adopt AI in production environments. 

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 building a high-performance AI inference platform for developer-native teams running latency- and cost-sensitive workloads at scale.

In AI infrastructure, PoC success does not guarantee production success. This role ensures that what we commit to is scalable, efficient, and aligned with platform strategy.

We are looking for a Presales Architect to become a foundational technical partner to our customers and a force multiplier for Sales and Engineering. You will shape complex AI workloads from first discovery through production feasibility validation, ensuring technical rigor, economic viability, and scalable architecture decisions.

You will operate at the intersection of customer ambition, engineering reality, and commercial growth, influencing:

• Revenue quality
• Engineering focus
• Product evolution
• Customer trust at scale

You’re welcome to work remotely from Europe.

Your responsibilities will include: 

Strategic Technical Discovery

• Lead deep technical discovery with engineering teams and technical founders
• Understand model requirements, traffic expectations, latency constraints, GPU economics, and system dependencies
• Translate customer ambition into production-feasible architectures
• Identify hidden technical risks early

Commercial Acceleration

• Partner tightly with Sales on strategic deals
• Influence deal strategy through architectural clarity
• Prevent misaligned commitments before engineering allocation
• Increase PoC-to-production conversion by ensuring technical realism

PoC Architecture & Validation

• Define measurable success criteria (latency, TTFT, throughput, cost envelope)
• Classify workload complexity and required optimization depth
• Align appropriate resources (ML Solution Architects, engineering, GPU capacity, etc.)
• Drive structured Go / No-Go decisions
• Prevent uncontrolled customization or hidden R&D

Pattern Recognition & Platform Leverage

• Identify recurring configuration patterns across customers
• Quantify demand for advanced optimizations (quantization, speculative decoding, etc.)
• Surface structured insights to Product and Engineering
• Help evolve platform capabilities based on real workload data

We expect you to have: 

• Deep understanding of AI inference systems and GPU-backed infrastructure
• Experience with LLM workloads and performance-sensitive environments
• Experience with inference frameworks and libraries (e.g., vLLM, SGLang, TensorRT-LLM).
• Ability to reason about latency, throughput, cost, and architecture tradeoffs
• Strong customer presence with engineering-first organizations
• Comfort challenging assumptions and pushing back constructively
• Commercial awareness – you understand that engineering time is a strategic resource

Preferred technical stack: 

• Programming Languages– Python
• Frameworks and Libraries– vLLM, SGLang, TensorRT-LLM, OpenAI/Anthropic SDKs
• Frameworks for Agentic Pipelines : Langchain / Langsmith / smolagents / equivalent
• API and Web Frameworks– FastAPI, Flask
• MLOps and DevOps tools– Kubernetes (K8s), Docker, Git
• Cloud Platforms– AWS (SageMaker, Bedrock), GCP (Vertex AI), Azure (Azure ML)

What success looks like: 

• Strategic deals are technically sound before engineering engagement
• PoCs are clearly scoped and economically justified
• Engineering capacity is allocated predictably
• Conversion to production improves
• Customers view you as a trusted architectural advisor

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

Your responsibilities:

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

Must-haves:

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

Nice-to-haves:

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

We conduct coding interviews as part of the process.

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

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

Your responsibilities will include: 

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

We expect you to have: 

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

The Role

Your responsibilities will include:

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

We expect you to have:

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

It will be an added bonus if you have:

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

We conduct coding interviews as part of the process.

The role

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 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.

The role

We're looking for a Technical Account Manager (TAM) to help our customers successfully transition from proof-of-concept to production and scale their AI workloads on Nebius infrastructure.

This role sits at the intersection of engineering, delivery, and customer success – ensuring that what was promised during pre-sales actually works reliably in production. You will work closely with customer engineering teams, Solution Architects, and Product/Infrastructure teams to drive stable, performant, and cost-efficient deployments.

This role is NOT:

• A sales role (though you will support expansion through value)
• A pure support role (you won’t just react to tickets)
• A solution architect role (you won’t design systems from scratch)

You’re welcome to work remotely from Europe.

Your responsibilities will include: 

• Own the production journey
  • Lead the transition from PoC to production
  • Ensure customer workloads are deployed, stable, and scalable
  • Drive time-to-production and time-to-value
  
  
• Ensure technical success in production
  • Understand customer architectures and use cases
  • Monitor and improve:
  o performance (latency, throughput)
  o cost efficiency
  o reliability
  • Identify and resolve bottlenecks proactively
  
  
• Act as a trusted technical partner
  • Work directly with customer engineering teams
  • Provide guidance on best practices and optimisation
  • Translate technical challenges into actionable solutions
  
  
• Manage risks and incidents
  • Act as a primary technical contact for production issues
  • Coordinate with internal teams to resolve incidents
  • Communicate clearly during high-pressure situations
  
  
• Drive continuous improvement
  • Identify opportunities to optimise and expand usage
  • Provide structured feedback to Product and Infrastructure teams
  • Help shape better solutions based on real customer needs

We expect you to have: 

• Technical background
  • Solid understanding of:
  o cloud or infrastructure systems
  o distributed systems or high-load applications
  o AI/ML workloads (LLMs, inference, etc.) is a strong plus
  • Ability to troubleshoot and reason about system performance
  
  
• Customer-facing experience
  • Experience working directly with technical customers (e.g. engineers, ML teams)
  • Ability to communicate complex topics clearly and effectively
  
  
• Ownership & execution
  • Strong sense of ownership – you drive outcomes, not just tasks
  • Ability to manage multiple customers and priorities
  • Structured, proactive, and solution-oriented mindset

It will be an added bonus if you have: 

• Experience with GPU workloads or AI infrastructure
• Familiarity with inference frameworks (e.g. vLLM, TensorRT, etc.)
• Background in solutions engineering, SRE, or technical support in B2B environments

The role

We are seeking a highly skilled and customer-focused professional to join our team as a Solutions Architect specializing in Cloud infrastructure and MLOps. As a Cloud Solutions Architect, you will play a pivotal role in designing and implementing cutting-edge solutions for our clients, leveraging cloud technologies for ML/AI teams and becoming a trusted technical advisor for building their pipelines.

You’re welcome to work from any DACH country (Germany, Austria, Switzerland).

Your responsibilities will include: 

• Act as a trusted advisor to our clients, providing technical expertise and guidance throughout the engagement. Conduct PoC, workshops, presentations, and training sessions to educate clients on GPU cloud technologies and best practices.
• Collaborate with clients to understand their business requirements and develop solution architecture that align with their needs: design and document Infrastructure as code solutions, documentation and technical how-tos in collaboration with support engineers and technical writers.
• Help customers to optimize pipeline performance and scalability to ensure efficient utilization of cloud resources and services powered by Nebius AI.
• Act as a single point of expertise of customer scenarios for product, technical support, marketing teams.
• Assist to Marketing department efforts during events (Hackathons, conferences, workshops, webinars, etc.)

We expect you to have: 

• 5+ years of experience as a cloud solutions architect, system/network engineer, developer or a similar technical role with a focus on cloud computing
• Strong hands-on experience with IaC and configuration management tools (preferably Terraform/Ansible), Kubernetes, skills of writing code in Python
• Solid understanding of GPU computing practices for ML training and inference workloads, GPU software stack components, including drivers, libraries (e.g. CUDA, OpenCL)
• Excellent communication skills, fluency in German or French preferred
• Customer-centric mindset

It will be an added bonus if you have: 

• Hands-on experience with HPC/ML orchestration frameworks (e.g. Slurm, Kubeflow)
• Hands-on experience with deep learning frameworks (e.g. TensorFlow, PyTorch)
• Solid understanding of cloud ML tools landscape from industry leaders (NVIDIA, AWS, Azure, Google) 

The role

The Security Engineering Team within the Platform Security organization is responsible for the strategic selection, implementation, management, and optimization of cybersecurity tools and technologies that improve security capabilities of the organization's platform. This team is instrumental in fortifying the security posture, proactively identifying and responding to security threats, ensuring the resilience and protection of critical data, systems, and services.

We are looking for an Infrastructure Security Engineer to secure our cloud and on-premises infrastructure by implementing security controls, monitoring threats, ensuring compliance with industry standards and respond to security incidents. The ideal candidate has a strong background in cloud security, Linux hardening, and network security.

Your responsibilities will include:

• Design and implement security measures to protect cloud and on-premises infrastructure.

• Identify and remediate vulnerabilities in cloud environments, networks, and operating systems.

• Build and maintain cloud and infrastructure security tools.

• Perform security reviews, threat modeling and risk assessments of infrastructure components.

• Develop and maintain security guidelines for Network and SRE teams.

• Collaborate with Network and SRE teams to integrate security best practices into their processes and systems.

• Stay updated on the latest security threats, vulnerabilities, and mitigation techniques.

• Serve as an network and infrastructure security subject matter expert to other teams.

We expect you to have:

• 4+ years of experience in network, infrastructure or cloud security.

• Strong understanding of modern cloud architectures and deployment models (VMs, containers, serverless, Kubernetes).

• Solid knowledge in networks, distributed systems and Linux systems engineering.

• Hands-on experience with network, VPN and Linux security.

• Understanding of Identity and Access Management (IAM) systems.

• Experience with security automation tools and scripting (e.g. Python, Bash, Go, etc.) and willingness to learn Go, if necessary.

• Experience in using and accessing security of Infrastructure as Code (Terraform).

• Experience in hardening Linux based systems (apparmor, seccomp, etc.).

• Experience in hardening Kubernetes.

• Strong problem-solving and analytical skills.

• Good written and verbal communication skills in English.

• Willingness to learn new things.

• Being comfortable working independently.

It will be an added bonus if you have:

• Proficiency in securing AWS, GCP, or Azure environments.

• Experience in conducting threat-modeling sessions.

• Experience in designing, building, and maintaining Identity Aware Proxies or Bastion hosts.

• Experience in translating compliance and regulation requirements into technical specifications.

• Experience in exploiting vulnerabilities in Linux kernel, VMs, containers, and networks.

• Experience in securing bare metal workloads.

• Security certifications such as OSCP or CKS.

We conduct coding interviews as part of the process.

The role

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

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

We expect you to have:

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

It would be an added bonus if you had:

• Experience designing high-load and scaling services

We conduct coding interviews as part of the process.

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

The role 

We are looking for a detail-oriented and reliable Customer Services Specialist to handle customer requests that directly impact core business processes, including:
 • GDPR / data protection requests
 • Billing and financial inquiries
 • Financial operations workflows
 • Basic technical support
This role requires a high level of ownership and autonomy, as many requests involve sensitive data (e.g., GDPR, data privacy) and must be handled with precision and care.
The ideal candidate is a self-starter, comfortable working independently, while also identifying opportunities to improve processes and increase operational efficiency.

Responsibilities
  • Manage tickets end-to-end: intake, categorization, analysis, and resolution via Jira
 • Handle GDPR requests: logging, documentation, coordination, and timely completion
 • Support billing and finance workflows: invoice validation, clarifications, refunds, and adjustments
 • Assist with financial operations processes within defined frameworks
 • Provide basic technical support and escalate when needed
 • Ensure strict adherence to SLAs, processes, and internal guidelines
 • Maintain high-quality escalations with clear, complete, and accurate information
 • Identify inefficiencies and propose improvements to workflows and recurring request handling

Requirements
• Previous experience in customer support / L1 technical support or a similar role
 • Hands-on experience with ticketing systems (e.g., Jira)
 • Strong understanding of filters and dashboards (Jira or similar)
 • Experience working with CLIs (e.g., AWS CLI or similar) is a plus
 • Strong ability to follow processes and ensure compliance
 • High attention to detail and accuracy when handling data
 • Strong communication skills and customer-oriented mindset
 • Ability to work independently and take ownership of tasks from start to finish
 • Structured, proactive mindset with a focus on efficiency and continuous improvement

Nice to Have
 • Experience handling GDPR requests or knowledge of data protection regulations
 • Understanding of financial operations in SaaS / IT environments
 • Background in billing (invoices, refunds, credit notes)

The role

We are scaling AI workloads across PoC and production environments.

As we grow, operational clarity and structured delivery become critical. We are hiring a Delivery Operations Manager to strengthen launch readiness, improve cross-team coordination, and manage operational relationships with external infrastructure vendors.

You will play a key role in strengthening operational excellence as we scale AI delivery across increasingly complex infrastructure environments.

You’re welcome to work remotely from Europe.

Your responsibilities will include: 

Delivery Operations & Launch Readiness

• Maintain operational visibility across active PoCs and production workloads
• Establish lightweight launch readiness standards for production rollouts
• Ensure workload expectations, ownership, and escalation paths are clearly defined
• Reduce last-minute surprises in customer-facing launches

External Vendor Management

• Coordinate operational relationships with external and infrastructure vendors
• Track contracted capacity and provisioning timelines
• Monitor vendor performance and escalation workflows
• Partner with Legal and Finance on infrastructure-related agreements and follow-ups

Cross-Functional Alignment

• Improve clarity across Sales, Pre-Sales, Engineering, and Delivery handoffs
• Support structured weekly operational reviews
• Surface risks early and drive resolution across teams

You may be a good fit if: 

• You have experience in cloud, AI, or infrastructure-heavy environments
• You are comfortable working with technical teams
• You have managed external vendors or infrastructure partners
• You bring structure without adding bureaucracy
• You are proactive in surfacing risks and improving execution discipline

What success looks like: 

• Production launches are structured and predictable
• Active PoCs and workloads are visible and tracked
• External infrastructure vendors operate within clear expectations
• Cross-team delivery friction is reduced

The role 

Nebius is building next-generation AI infrastructure at scale. We are looking for a Field Technical Lead to drive on-site execution of new data center deployments, leading technical teams and contractors while ensuring high-quality, on-time delivery. This position requires frequent travel to data centers during key deployment phases. The person in this role can be located anywhere in the EU or UK but must be available for regular travel to data center deployments around EU/UK. 

Your responsibilities will include: 

• Technically lead on-site deployment of GPU-based compute clusters, storage systems, and high-speed networking in data centers.
• Support Project Managers in planning, coordinating, and tracking project delivery activities.
• Organize and supervise contractors, vendors, and internal technical teams to ensure smooth execution of deployment workstreams.
• Proactively identify, troubleshoot, and resolve technical and operational issues during deployments.
• Maintain clear and accurate project documentation, including deployment plans, risk logs, issue trackers, and acceptance reports.
• Ensure transparent communication with all stakeholders by providing regular status updates, escalating blockers, and managing expectations.
• Collaborate closely with cross-functional teams including engineering, networking, operations, and supply chain.
• Participate in related project activities such as automation initiatives, process improvements, and post-deployment support when required.

We expect you to have: 

• Proactive, ownership-driven leader with the ability to anticipate issues, drive decisions on-site, and lead teams through complex deployments.
• Proven hands-on experience with data center infrastructure deployments, ideally in high-performance computing or AI-focused environments.
• Strong understanding of data center operations including racking, structured cabling, power planning, and cooling considerations.
• Technical knowledge of GPU servers, compute nodes, storage platforms, and high-speed networking technologies.
• Experience working within project delivery frameworks, collaborating closely with Project Managers, and managing subcontractors or vendors.
• Excellent problem-solving skills with the ability to troubleshoot and resolve issues in on-site, time-critical environments.
• Strong communication skills in English, both written and verbal.
• Ability to document processes, maintain tracking systems, and produce clear, structured deployment and status reports.

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.

Role Overview
The Sales Operations Specialist plays a key role in enabling revenue execution by supporting the end to end deal operations process. The role focuses on ensuring that sales agreements are accurately translated into 
contracts, billing configurations, and internal systems while maintaining operational accuracy, pricing compliance, and smooth cross-functional coordination. You will handle both routine and non-standard operational cases, collaborating with crossfunctional teams to ensure smooth sales support.

Key Responsibilities
- Play a key role in the contracting cycle by ensuring accuracy and compliance across sales requests, contracts, and billing setup.
- Support billing processes including mechanics, configurations, and tool management to ensure accurate invoicing.
- Review and validate sales requests to make sure contractual terms and billing details are correctly reflected in internal systems.
- Handle both routine and non-standard operational cases, providing solutions and escalating issues when needed.
- Learn and apply billing cycle processes and configuration basics in Nebius systems.
- Support billing accuracy and coordinate with Finance regarding invoice or payment discrepancies.
- Assist with sending reminders for overdue or partial payments.
- Participate in the NBA Ops Channel on-call rotation under supervision, handling routine cases.
- Support preparation of standard payment and operations reports.
- Collaborate with Sales, Support, and Finance teams to resolve straightforward client or internal issues.
- Ensure proper documentation and smooth communication across teams.
- Ensure adherence to pricing guidelines and margin policies when processing sales requests and contracts.
- Drive operational follow-ups with internal stakeholders to ensure deals progress without operational blockers.
- Identify operational gaps or blockers in deal execution and escalate proactively
- Partner closely with Sales teams to ensure operational readiness and smooth deal execution.

Key Qualifications & Experience
Must-have requirements:
- Up to 2 years of experience in sales operations, billing, finance, or a related role 
- Experienced with billing or CRM & ERP tools (e.g., Net.Suite, Salesforse, Hubspot)
- Understands the commercial impact of operational decisions, including pricing and margin considerations.
- Strong attention to detail and willingness to learn.
- Good organizational and communication skills.
- Good communication skills in English

Preferred qualifications:
- Experience in SaaS or technology companies.
- Exposure to contracts, invoices, or payments processes.

Competencies & Behavioral Traits
- Demonstrate curiosity and willingness to learn new processes, systems, and tools.
- Accurately track data and ensures correctness in billing and payments.
- Work effectively with peers and cross-functional teams under guidance.
- Take responsibility for assigned tasks and seeks support when needed.
- Handle routine cases and adapts to new processes with supervision

•  Initiating and driving cross-team projects with clear goals and timelines
• Aligning conflicting priorities and stakeholder needs, including C-level
• Facilitating technical and procedural decision-making
• Establishing and scaling repeatable processes
• Collaborating closely with engineering, infrastructure, and business teams

• Proven experience leading technical projects or engineering teams
• Strong technical background: software architecture, infrastructure, networking
• Experience with Kubernetes
• Strong communication and analytical skills
• Demonstrated coding ability, confirmed during the interview process

The role

Nebius is looking for a part-time, project-based role (~20h/week) focused on building a scalable approach to internal learning. You’ll define how learning content should work: structure, flow, clarity, and visual system. 

About our style 

We already have a corporate design system for business content, and your role is to build a scalable learning experience within these constraints. 

We value: 

• clarity over decoration;
• minimalism over visual noise;
• structured thinking over “pretty screens”.   

Your responsibilities will include: 

• Collaborating with L&D (product) to understand content structure and learning objectives;
• Designing the UX of SCORM-based courses, including text layout and interactive elements (quizzes, case studies);
• Developing a course concept and template aligned with the existing corporate design system;
• Creating 3 full courses using this framework;
• Designing illustrations or establishing their visual system (style, asset library, or generation prompts);
• Ensuring brand consistency and a clean, intuitive user experience;
• Iterating on designs based on stakeholder feedback. 

We expect you to have: 

• Experience as a UX, product, or learning designer;
• Background working with educational content or courses (a strong plus);
• Ability to translate complex ideas into simple, structured user flows;
• Strong visual sensibility: clean, modern, minimalistic;
• Comfort working within constraints like an existing design system;
• Familiarity with SCORM and e-learning basics, or the ability to ramp up quickly;
• A self-directed work style with confidence making design decisions independently. 

It will be an added bonus if you have: 

• Experience designing with learning metrics in mind: completion rates, drop-off points, time-to-complete, and quiz success rates. 

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.