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

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 the United Kingdom.

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
• 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

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

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

You’re welcome to work remotely from Europe.

Your responsibilities will include:

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

We expect you to have:

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

It will be an added bonus if you have:

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

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

Regional GTM Recruiting Manager, EMEA & APJ 

The role 

As the Regional GTM Recruiting Manager for EMEA and APJ, you own how we build and scale our Go To Market teams across the region. 

You are accountable for hiring across Sales, Marketing, Partnerships and Customer functions, ensuring we attract and hire the talent required to support regional expansion and market development. 

Reporting to the Head of GTM Talent, you will lead and develop the EMEA and APJ recruiting team while acting as a strategic partner to regional and global GTM leadership. You will bring structure to regional headcount planning, strengthen hiring quality and ensure we are building teams thoughtfully and sustainably across multiple markets. 

This role is remote within EMEA or APJ and works closely with stakeholders across global time zones. 

Responsibilities 

• Own GTM recruiting strategy and execution across EMEA and APJ 

• Lead and develop the regional recruiting team, driving accountability, performance and consistent hiring practices 

• Partner with global and regional commercial leadership to align hiring strategy with revenue targets and expansion priorities 

• Bring structure to workforce planning, sequencing hires based on business impact, regional priorities and market maturity 

• Support hiring for both established markets and emerging regions as Nebius expands its commercial footprint 

• Build scalable recruiting processes that support growth across multiple countries and regulatory environments 

• Partner with HR and regional leadership to ensure hiring practices align with local employment regulations and market conditions 

• Elevate hiring standards through structured assessment and hiring manager enablement 

• Develop proactive sourcing strategies for high impact and leadership level commercial roles across regional talent markets 

• Use hiring data and market insights to guide prioritisation and recruiting investment across countries 

• Ensure an efficient and high quality candidate experience across all GTM hiring activity 

• Step in as a player coach on strategic or senior searches when needed 

What success looks like 

• A high performing GTM recruiting team delivering against regional growth priorities 

• Hiring plans aligned with revenue objectives and regional expansion milestones 

• Clear prioritisation of revenue critical roles across markets 

• Strong commercial hires that improve execution and strengthen leadership depth across EMEA and APJ 

• Consistent recruiting standards across countries while adapting to local talent markets 

Experience & Qualifications 

• Higher education degree 

• Proven experience managing recruitment teams in high growth technology or SaaS environments 

• Strong track record hiring across Sales, Marketing, Partnerships and Customer functions 

• Experience hiring across multiple countries or international markets 

• Clear understanding of commercial organisation design and revenue team scaling 

• Experience partnering directly with senior commercial leaders 

• Ability to bring structure and prioritisation to complex and fast moving growth environments 

• Data informed mindset with comfort using recruiting metrics and market insights 
• Strong leadership presence and stakeholder influence 

• 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

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.

• 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!

Role Overview

The Corporate Development Manager – Capital Markets plays a central role in shaping and executing Nebius’s capital formation strategy across debt, equity-linked, asset-backed, and structured capital solutions. This role is responsible for supporting the company’s rapid expansion through financing strategy, transaction execution, and capital structure analysis.

The position requires strong technical expertise in capital markets, sound commercial judgment, and the ability to work effectively with senior internal stakeholders and external financing counterparties. The role will work closely with leadership as well as cross-functional teams including Legal, Finance, Treasury, Operations, and Infrastructure. Depending on business priorities, the role may also support selective M&A and strategic investment activity.

Key Responsibilities

• Manage end-to-end execution of financing transactions across debt, equity-linked, asset-backed, and structured capital solutions.
• Support the development of Nebius’s capital structure strategy, including assessment of trade-offs across cost of capital, maturity profile, flexibility, and dilution.
• Build and maintain detailed financial models to evaluate leverage capacity, scenario outcomes, and financing alternatives.
• Prepare high-quality board-level materials, financing proposals, and investment memoranda.
• Lead cross-functional execution workstreams for complex financing transactions, coordinating internal stakeholders and external advisors.
• Act as a key point of contact with financing counterparties and other external stakeholders during transaction processes.
• Provide analytical support on broader corporate development initiatives, including selective M&A and strategic investment opportunities where relevant.
• Mentor and support the development of junior members of the Corporate Development team.
• Contribute to improving internal decision-making through clear analysis, strong commercial insight, and disciplined execution.

Key Qualifications & Experience

• 7–10 years of relevant experience in investment banking, including DCM, ECM, Leveraged Finance, Structured Finance, or private credit.
• Proven track record of independently leading financing transactions from structuring through closing.
• Strong experience across both US and European capital markets.
• Deep expertise across debt, equity-linked, asset-backed, and structured capital products.
• Advanced financial modelling skills, including capital structure analysis, leverage assessment, and multi-scenario stress testing.
• Strong ability to prepare clear and credible materials for senior leadership and board-level audiences.
• Experience managing multiple high-priority workstreams in fast-paced, international environments.
• Strong stakeholder management skills and confidence in engaging with internal leadership and external financing partners.
• High level of ownership, judgment, and ability to operate effectively in ambiguity.

Preferred qualifications:

• Experience in AI, high-growth technology, or digital infrastructure sectors.
• Exposure to M&A processes and transaction evaluation.
• Understanding of post-deal integration considerations and broader corporate development activity.
• Prior experience mentoring or developing junior team members.

Competencies & Behavioural Traits

• Strong analytical capability with a high level of financial and commercial rigor.
• Excellent judgment and decision-making in complex, high-stakes situations.
• High ownership mindset and ability to drive work-streams independently.
• Strong communication skills, including the ability to influence senior stakeholders and present complex topics clearly.
• Ability to collaborate effectively across functions, teams, and geographies.
• Resilience and effectiveness in fast-paced, high-growth environments.
• Structured problem-solving and ability to balance detail with strategic perspective.
• Professional credibility and maturity when representing the company externally.

New data center development:

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

The role

As an IT Technician, you will play a vital role in maintaining and optimizing the IT infrastructure within our data center. This includes working hands-on with modern technologies such as the advanced H200 GPU cloud cluster. Your responsibilities will encompass supporting the data center’s IT infrastructure, troubleshooting and resolving hardware issues, and ensuring the smooth operation of critical systems.

You’re also welcome to work on-site at our colocation facility in Longcross, UK.

Your responsibilities will include:

• Diagnosing and resolving issues related to IT hardware and ensure the continuous support of the data center’s IT infrastructure.
• Collaborating effectively with internal teams and external contractors to address technical and operational challenges.
• Installation, upgrading and dismantling of hardware based on operational requests and requirements.
• Managing and maintaining the connectivity of fiber optic cables and patch cords.
• Planning, executing and monitoring regular IT tasks to maintain and improve IT infrastructure operations.
• Processing Return Merchandise Authorizations (RMAs) in compliance with established manuals and procedures.
• Developing clear and comprehensive documentation and manuals for hardware configuration, troubleshooting and maintenance.
• Collaborate with key stakeholders, including (teams, executives).
• Lead and manage (specific workflows, processes, projects).
• Monitor and evaluate progress on (specific projects).

We expect you to have:

• 3+ years of hands-on experience in diagnosing and resolving server hardware issues.
• A solid understanding of data center operations, as well as server and network equipment principles.
• Basic proficiency in the Linux operating system and familiarity with command-line tools.
• Practical experience working with server IT hardware, enterprise-grade network switches and fiber optic cables.
• Excel skills, including proficiency with pivot tables, formulas, lists and graph creation.
• A proactive, responsible and goal-oriented approach to work.

It will be an added bonus if you have:

• Driving License (Category B)
• Project planning skills

The role

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

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

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

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

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

Some examples of what your responsibilities might include are:

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

We expect you to have:

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

Nice to have:

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

About the 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

We are opening a 3–6 month Early Career program within our AI R&D team. You will work alongside experienced researchers to solve challenges in LLMs, reinforcement learning, and agentic systems.

We are looking for Early talents to support research in:

• Reinforcement learning for agents and reasoning models
• Building reinforcement learning environments
• Efficient model distillation and evaluation

Your responsibilities will include:

• Assist in designing and running experiments to train LLMs and speculators for them
• Help analyze experimental results and document findings
• Write and maintain code for data mining, processing, and model evaluation
• Collaborate with the team to explore new methods in the selected research direction
• Participate in technical discussions and discuss future steps of research
• Advanced methods for efficient speculative decoding
• Inference optimization techniques

We expect you to have:

• Strong knowledge of computer science and machine learning fundamentals
• Experience with Python and familiarity with deep learning frameworks
• Ability to write clean, efficient code
• Strong problem-solving skills and a willingness to learn quickly
• Good communication skills in English
• Permitted to work in the job’s location

Nice to have:

• Previous experience with NLP/reinforcement learning/AI agents projects
• Familiarity with current LLM concepts
• Enrollment in or completion of a degree in Computer Science, AI, or a related field
• Contributions to open-source projects

What we offer

• Competitive salary and comprehensive benefits package
• Mentorship from experienced AI, ML, and cloud infrastructure professionals
• Hands-on experience with real customer workloads and production systems
• Remote work flexibility and a collaborative, supportive team environment
• Opportunity to be considered for a full-time role after the Early Talent Program

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

The role 

Nebius is 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.

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

Nebius is looking for a Site Security Manager.  The DC (Data Centre) Physical Security Manager is responsible for overseeing and managing the physical security measures to protect the data center facility in Lille, personnel, and assets. This role involves planning, implementing, and monitoring security protocols, systems, and procedures for the on-site security team against unauthorized access, theft, vandalism, and other security threats.

Your responsibilities will include: 

• Security Planning and Strategy:
• Conduct risk assessments and vulnerability analyses to identify potential security threats and weaknesses.
• Develop and implement comprehensive physical security plans and policies for DC. 
• Security team management
• Recruit, train, and supervise the security team personnel, ensuring they are well-equipped and educated to perform their duties effectively.
• Conduct regular training sessions on security protocols, emergency response procedures, and the use of security equipment.
• DC staff training and briefing: 
• Performing background checks on our DC staff before onboarding. 
• Brief and train the DC staff in physical best practice security behavior. 
• Access Control Management:
• Oversee the installation, maintenance, and operation of access control systems.
• Create strict access control policies to ensure no unauthorized people are entering.  
• Monitor and review access logs and reports to detect and respond to suspicious activities.
• Visitors, Suppliers and contractors Management:
• Determine and implement protocols for treating visitors and suppliers to maintain a secure environment.
• Determine the security level for each Visitor or Vendor entering the site
• Incident Response and Investigations:
• Develop and maintain incident response plans and protocols for various security scenarios, including unauthorized access, theft, and emergencies.
• Lead investigations into security incidents, coordinating (If needed, with law enforcement and other relevant authorities).
• Security System Maintenance:

• Overall responsibility for the DC’s security systems and our Security Systems admin. 
• Collaborate with IT and facilities teams to integrate security systems with other data center infrastructure.
• Manage contracts and relationships with security system vendors and service providers.

We expect you to have: 

• Experience in security operations management, preferably in big corporations or governmental systems.  
• Strong leadership and communication skills with the ability to effectively manage a diverse security team.
• Knowledge of security principles, practices, and regulations, including relevant laws and industry standards in France. 
• Experience with security technologies like CCTV, access control systems, and security software.
• Analytical and problem-solving skills to assess security risks and develop appropriate responses.
• Ability to work under pressure and make sound decisions in emergencies.

The role

We are seeking a Regulatory Counsel to join the Ethics and Compliance team to support our trade controls program across the US and EMEA operations. In this role, you will provide strategic advice on global trade controls, including export controls and sanctions, while also contributing to emerging regulatory challenges affecting AI, cloud, and digital infrastructure (including data center operations).

You will work cross-functionally with product, engineering, sales, and operations teams; coordinate with outside counsel on complex regulatory matters; and have significant latitude to shape our approach to regulatory challenges. We’re a remote-first organization with global team members, so you’ll need to be comfortable working across time zones and cultures.

Your responsibilities will include: 

• Advise on US export control (EAR) and sanctions (OFAC) compliance, as well as EU/UK export controls or sanctions where applicable, for AI cloud infrastructure services, including license exception eligibility and deemed export considerations.
• Provide legal guidance on escalated restricted party screening issues and advise on regulatory risks associated with business partner onboarding and transaction reviews.
• Advise on export classifications, licensing assessments, jurisdiction and classification, deemed export compliance, and foreign national access to controlled technology.
• Advise on export control implications of cross-border technology transfers and access to controlled technical data across US and EMEA jurisdictions.
• Monitor regulatory developments (US, UK, EU, and relevant member-state regimes) affecting technology exports, sanctions regimes, AI systems, and cloud services; assess impact and recommend policy responses.
• Advise on compliance processes, policies, and internal guidance materials; coordinate with outside counsel as needed.
• Collaborate with stakeholders to integrate compliance into business operations; support regulatory incident response, including internal reviews related to potential export controls or sanctions issues.

We expect you to have: 

• JD from an accredited law school and admission to practice in at least one U.S. jurisdiction (or eligibility to in-house registration); UK/EU qualifications considered.
• 3-6 years of relevant experience. Familiarity with encryption classifications (e.g., License Exception ENC) is a plus.
• Demonstrated ability to apply complex regulations to products, services, and business operations and advise on applicable regulatory risks.
• Excellent analytical, written, and verbal communication skills, stakeholder management, and ability to explain complex regulations to technical and business audiences, including working effectively across time zones with globally distributed teams.
• High level of integrity and ability to manage multiple priorities in fast-paced environment.

It will be an added bonus if you have: 

• Experience in a highly regulated, high-growth, or global technology environment.
• Experience with national security-related technology controls or review processes is a plus.

We are looking for someone business-minded who is forward-thinking, pragmatic, and comfortable with uncertainty.

We offer competitive salaries, ranging from 156k - 236k OTE (On Target Earnings) + equity based on your experience.

The role

We are looking for an Event Manager, EMEA to support the planning and delivery of high-quality marketing events across the region. 

This is a hands-on, execution-focused role where you will help bring events to life—from logistics and vendor coordination to on-site delivery and post-event follow-up. You will work closely with regional marketing, sales, and global teams to ensure events are delivered smoothly, on time, and aligned with Nebius’ brand and business goals.

This role is ideal for someone who thrives in a fast-paced environment, enjoys managing details, and wants to build experience in B2B event marketing within the AI and cloud space.

What you’ll gain:

• Hands-on experience executing high-impact events in the AI and cloud space
• Exposure to global marketing and sales teams
• Opportunity to grow into a more strategic field marketing role over time

You’re welcome to work remotely from the United Kingdom.

Your responsibilities will include: 

• Event Planning & Execution
  - Support the end-to-end execution of regional events including industry conferences, hosted events, workshops, and partner activations
  - Coordinate logistics such as venue sourcing, catering, travel, AV, branding, and on-site setup
  - Manage event timelines, checklists, and deliverables to ensure smooth execution
  - Provide on-site support at events, ensuring a high-quality attendee experience
  
  
• Vendor & Agency Coordination
  - Work with external vendors, agencies, and venues to support event delivery
  - Track timelines, deliverables, and budgets to ensure projects stay on schedule
  - Assist with contract coordination and invoice processing
  
  
• Cross-Functional Support
  - Collaborate with regional marketing, sales, and partner teams to support event goals and attendee targeting
  - Coordinate with internal teams (design, content, operations) to ensure all event assets are delivered on time
  - Support speaker logistics, briefing materials, and presentation coordination
  
  
• Campaign & Attendee Management
  - Assist with event promotion, registration tracking, and attendee communications
  - Maintain accurate event data in CRM and marketing systems
  - Support lead capture and post-event follow-up processes
  
  
• Reporting & Operations
  - Track key event metrics such as attendance, leads, and engagement
  - Assist in post-event reporting and feedback collection
  - Support budget tracking and expense management across events

We expect you to have: 

• ~4 years of experience in event marketing, event coordination, or field marketing (preferably in B2B tech, SaaS, or related industries)
• Strong organizational and project management skills with high attention to detail
• Experience supporting in-person and/or virtual events
• Ability to manage multiple projects simultaneously in a fast-paced environment
• Strong communication and collaboration skills across internal teams and external vendors
• Familiarity with marketing tools such as Salesforce, HubSpot, Marketo, or similar is a plus
• Interest in AI, cloud, or technology industries is preferred
• Bachelor’s degree in Marketing, Business, or a related field

Additional requirements: 

• Willingness to travel up to 25% for events across EMEA
• Comfortable working across time zones and supporting regional initiatives

The role 

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

Your responsibilities: 

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

Must-haves: 

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

Nice-to-haves: 

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

We conduct coding interviews as part of the process.

• Own and build Nebius’ ISV partner ecosystem from the ground up with your key target accounts — defining strategy, segmentation, onboarding models, and long-term growth frameworks
• Identify, recruit, and close high-impact AI and ISV partners that can drive net-new customer acquisition and revenue growth
• Develop and scale repeatable co-sell motions, embedding partners into Nebius’ core sales plays and strategic opportunities
• Drive partner-sourced and partner-influenced pipeline, with a strong focus on net-new accounts and expansion
• Build structured frameworks for joint business planning, pipeline generation, forecasting, and performance management
• Lead joint go-to-market execution, ensuring partners are actively generating demand and influencing deals
• Drive partner technical readiness and platform adoption through onboarding, enablement, and joint solution development
• Act as a key architect of Nebius’ partner program, including co-sell models, incentives, and engagement frameworks
• Stay deeply connected to the AI ecosystem, identifying emerging players, trends, and high-leverage partnership opportunities
• Represent Nebius across industry events, ecosystem forums, and strategic partner engagements
• Serve as the voice of partners internally, working cross-functionally with Sales, Product, Engineering, Marketing, Legal, and GTM teams

• 10+ years of experience in partnerships, business development, or indirect sales within B2B technology
• Strong understanding of the AI/ML and cloud ecosystem (infrastructure, models, data pipelines, ISVs, tooling
• Proven track record of building partner ecosystems from early stages — not just managing existing relationships
• Demonstrated ability to source, negotiate, and close strategic partnerships that drive measurable business impact
• Proven success in driving net-new pipeline, opening new accounts, and scaling revenue through repeatable co-sell programs
• Experience leading co-sell and joint go-to-market motions with sales organizations
• Solid grasp of cloud platforms and consumption-based business models
• Technical fluency — able to engage in architecture discussions, use-case validation, and product alignment
• Builder mindset — comfortable operating in ambiguity and creating structure from scratch
• Strong executive presence with experience navigating complex, multi-stakeholder environments
• Excellent communication, negotiation, and prioritization skills

• Experience working closely with Product and Engineering teams to influence partner integrations and roadmap
• Background in AI-intensive industries such as Financial Services, Healthcare, Robotics, Retail, or Automotive

• You are building the ecosystem — not inheriting one
• Direct ownership of partner-driven revenue and growth
• High autonomy and visibility across the business
• Opportunity to shape how modern AI partnerships are defined and executed at Nebius

The role 

We’re building Nebius Token Factory — an AI inference platform that powers high-performance, cost-efficient workloads at scale. As a Senior Technical Product Manager, you’ll own one of our core product streams and drive it end to end: from roadmap and design to launch and adoption of features our customers rely on.

You are welcome to work remote from the UK, or hybrid from our Amsterdam location.

Your responsibilities will include: 

• Own the product roadmap, delivery and developer experience for one of our flagship product direction - Dedicated Endpoints for AI Models Inference
• Partner with engineering and research to design tools that let customers run large-scale, high-load inference workloads efficiently.
• Support sales & customers by preparing materials, leading PoCs/betas, and ensuring smooth onboarding of complex workloads.
• Drive product–market fit through continuous user research, customer interviews, and market & competitive analysis
• Manage technical partnerships and ensure integrations deliver measurable value despite limited resources.

We expect you to have: 

• 3–5 years of product management experience, shipping technical products with 10–15+ cross-functional stakeholders(engineering, research, design, support, marketing, legal, leadership).
• Hands-on mindset — a power user of your own product, comfortable diving into:
           AIOps lifecycle: inference, experimentation, evaluation, fine-tuning, deployment
           Cloud-native and DevOps tooling
           Distributed systems and production infrastructure
• Excellent execution and project management skills — roadmaps, milestones, ownership, Agile processes, sprints, and change management (without creating chaos).
• Outstanding communication — able to write crisp PRDs, RFCs, runbooks, and release notes; articulate constraints and trade-offs clearly to technical and non-technical teams.
• Technical fluency — able to speak the same language as engineering, define precise requirements, understand constraints, and make sensible trade-offs grounded in reality.
• B2B SaaS experience, ideally working with enterprise customers and technical buyer personas.
• Customer-obsessed — proactive in uncovering needs, understanding customer AI strategy, and ensuring our product becomes essential in their stack.
• Bias toward action — runs problems end-to-end without waiting for instruction, even with incomplete data.

The Product

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

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

The Role

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

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

In this position, your responsibility will be to

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

You may be a good fit if you:

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

Strong candidates may also have experience with:

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

We conduct coding interviews as part of the process.

The role

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.

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

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

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

In this position, you will be responsible to:

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

Examples of outcomes you could drive as a Team Lead

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

What you will bring to the table:

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

It would be an added bonus if you had:

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

• 5+ years of experience in technical recruitment, with a strong focus on senior-level hiring.
• Proven track record hiring in AI/ML, LLMs, Inference, distributed systems, HPC, infrastructure, GPU engineering, or related areas.
• Strong sourcing expertise and deep understanding of modern engineering roles, tech stacks, and motivations of senior candidates.
• Ability to operate autonomously in a fast-moving environment, balancing multiple complex searches.
• Excellent communication, stakeholder management, and analytical skills.
• Curiosity, creativity, and the ability to translate complex technical requirements into effective sourcing strategies.

The role

In a rapidly evolving world, trust in AI depends on AI agents being grounded in fresh, verified real-world data. Search is the foundation that makes this possible. In this role, you will define what quality means for a search system built for AI agents from day one.

In this position, your responsibility will be to

• Own search-related quality metrics end-to-end: from definition and computation to evolution and transition to next-generation metrics.
• Design and reason about analytics architecture across the full stack: runtime behaviour → data pipelines → metrics → dashboards.
• Develop and maintain analytics pipelines and tooling using Python.
• Translate product, user, and technical requirements into meaningful, actionable metrics.
• Challenge existing assumptions about quality and push for better, more reliable measurement.
• Work closely with product managers, engineers, and stakeholders to align analytics with system behavior and business goals.
• Debug metric anomalies, investigate quality regressions, and propose data-driven improvements.

We expect you to have

• Senior-level experience solving search or search-adjacent analytical problems.
• Strong exposure to quality metrics in at least one of the following areas:
  • search relevance (web, geo, product, offers),
  • ranking and freshness,
  • ads quality or feed ranking.
• Ability to think end-to-end across users, products, and technology, not just individual metrics.
• Solid foundation in mathematical statistics.
• Strong Python skills and a hands-on engineering mindset.
• Experience operating in ambiguous environments and driving solutions independently.
• Clear analytical judgment: understanding why a metric exists, how it evolves, and when it should be retired.
• Strong communication skills and the ability to align product, engineering, and client perspectives.