Nebius Group

Growth Marketing

• Optimize onboarding and activation flows
• Improve free-to-paid conversion rates
• Design and run A/B tests across product and landing pages
• Partner with product on in-app messaging and growth experiments
• Build lifecycle campaigns tied to product behavior
• Identify friction in the funnel and propose solutions
• Own experimentation roadmap and growth reporting

Growth Marketing Manager

Marketing Operations

• Own and manage marketing automation (HubSpot or similar)
• Maintain CRM structure, lifecycle stages, and lead routing
• Build and optimize lead scoring models
• Manage campaign tracking and attribution frameworks
• Ensure reporting accuracy and dashboard integrity
• Improve marketing workflows and automation
• Partner with Sales and RevOps to align systems
• Evaluate and manage marketing tech stack

Marketing Operations Manager

Vice President

• Own enterprise revenue for your region, including pipeline generation, forecasting, and bookings.
• Build and lead a team of Enterprise Account Executives, setting clear expectations and coaching them to consistently exceed targets.
• Drive complex enterprise sales cycles, partnering directly on strategic deals with senior buyers and executives.
• Develop territory and account strategies that prioritize high-value opportunities and expand into large enterprise accounts.
• Partner with Sales Engineering, Marketing, and Product to refine messaging, support enterprise prospects, and influence roadmap priorities.
• Establish scalable enterprise sales processes, including forecasting discipline, pipeline management, and deal inspection.
• Recruit and develop top sales talent, creating a culture of accountability, collaboration, and performance.
• Represent customer feedback internally, helping guide Tavily’s product and go-to-market strategy.

Regional VP

Machine Learning Engineer

• 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.

Senior Applied ML Engineer

AI Research Scientist

• Drive applied research across retrieval, ranking, and agent-centric search systems
• Design and improve multi-stage retrieval pipelines, including query understanding, rewriting, and reranking
• Develop approaches for grounding LLMs using real-time web data
• Define and implement evaluation methodologies and quality metrics for agent-native search
• Lead experimentation on modern retrieval techniques such as hybrid search, embedding-based systems, and cross-encoders
• Work closely with engineering teams to bring research into production at scale
• Analyse trade-offs across relevance, latency, and cost in large-scale systems
• Contribute to long-term research and product direction
• Mentor engineers and researchers and raise the technical bar of the team

Applied AI Research Lead

Technical Product Manager

• Define and own the product vision and roadmap for OLTP, vector, and in-memory database capabilities.
• Turn customer and market input into clear product specs, priorities, and delivery plans.
• Lead cross-functional execution with Engineering, SRE, Security, Solution Architecture, and GTM teams.
• Drive critical capabilities including replication, failover, indexing, backup/recovery, observability, and scaling.
• Shape AI-specific data patterns such as hybrid retrieval, low-latency memory access, and workload isolation.
• Use product and operational metrics to guide decisions and continuous improvement.
• Track ecosystem and competitor trends to keep Nebius differentiated in AI-native data infrastructure.

Technical Product Manager – Databases

Solutions Engineer

• Acting as the main technical interface for customers running workloads on Nebius GPU infrastructure.
• Supporting customers in deploying, configuring, and tuning GPU-based environments for performance and reliability.
• Investigating and resolving complex issues spanning hardware, networking, operating systems, and cluster-level behavior.
• Partnering with internal teams (data center operations, networking, platform engineering) to coordinate and drive resolution of customer-impacting issues.
• Converting customer requirements into practical architectures, configurations, and execution plans.
• Identifying opportunities to improve system performance, stability, and overall customer experience.
• Developing and maintaining technical documentation, including solution patterns, troubleshooting guides, and operational best practices.
• Contributing to continuous improvement by surfacing recurring issues, gaps, and optimization opportunities to internal teams.

Senior Solution Engineer/Architect – GPU Infrastructure

Technical Project Manager

• 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 Program Manager

• Define, implement, and continuously improve KPIs, metrics, and dashboards for data center operations.
• Establish tracking frameworks to monitor performance, incidents, and operational efficiency across teams.
• Lead operational reviews (weekly/monthly) to identify bottlenecks, inefficiencies, and improvement opportunities.
• Ensure visibility and accountability through structured reporting and data-driven insights.
• Standardize processes across sites, improving operational consistency, scalability, and efficiency.
• Collaborate with stakeholders to align operational performance with business goals and customer SLAs.

Senior Technical Program Manager – Data Center Operations

• Own reliability and performance opportunities across the Nebius stack: from bare metal to applications.
• Define product direction end-to-end: problem discovery → design → delivery → adoption.
• Drive cross-functional execution across compute, networking, storage, observability, platform, and hardware teams.
• Lead deep problem research using customer interviews, analytics, workload studies, and logs investigations.
• Identify and prioritize bottlenecks affecting large-scale training/inference performance and stability.
• Translate advanced ML/infrastructure research into practical, scalable product capabilities.
• Define and operationalize product metrics for cluster experience (e.g. reliability, efficiency, latency-to-start, utilization, throughput).

Technical Product Manager – Mission Control

General Counsel

• Draft, review, and negotiate a wide range of commercial agreements, including:
• Technology and AI-related agreements
• Software licensing and SaaS agreements
• Commercial services agreements
• Vendor, procurement, and supplier contracts
• Strategic partnership and collaboration agreements
• Provide legal support for complex commercial transactions and strategic business initiatives.
• Partner closely with business, product, procurement, and operational teams to deliver practical, business-oriented legal advice.
• Ensure company activities comply with applicable US laws, regulations, and internal policies.
• Develop and improve contract templates, internal processes, and playbooks for the US legal function.
• Manage external counsel where needed and coordinate legal workstreams across multiple ongoing projects.
• Identify legal risks in commercial transactions and help implement pragmatic mitigation strategies.
• Support cross-functional initiatives related to technology, AI deployment, and commercial operations.

Commercial Legal Counsel

Engineer

• Design, deploy, and operate DWDM-based transport networks across long-haul and metro environments
• Perform wavelength provisioning, optical power tuning, and amplification design (EDFA/Raman) to ensure optimal link performance
• Troubleshoot cross-layer issues spanning optical transport and IP/MPLS networks, including packet loss, latency, and signal degradation
• Execute fiber characterization and fault isolation using OTDR, OSA, and BERT tools across various span distances
• Work directly with production platforms (Ciena, Infinera, ADVA) for provisioning, upgrades, and incident resolution
• Develop and maintain Python-based automation for optical health checks, telemetry ingestion, and inventory synchronization
• Participate in network expansions and hardware deployments, including on-site support for critical rollouts and audits
• Collaborate with IP engineering teams to ensure alignment between optical transport and routing layers
• Drive root cause analysis and implement preventive measures to improve fleet-wide reliability and performance

DWDM-IP Engineer

Recruitment

• Partner with VP and Director-level leaders to translate business goals into smart, forward-looking hiring plans.
• Build and deliver candidate generation strategies that reflect market shifts and create diverse, long-term pipelines.
• Design inclusive, data-driven hiring processes that improve quality of hire and reduce bias.
• Lead programmatic hiring initiatives that help the wider team deliver faster and at scale.
• Advise leaders on Nebius’ positioning in the market and how we compete for top talent.
• Use insights to influence decisions on headcount planning, location strategy and org design.
• Champion exceptional candidate experience across every touchpoint.
• Coach and mentor recruiters and interviewers to develop strong, value-aligned hiring capability.

Corporate Services Recruiter

• Proactively identify and engage senior-level engineers and researchers across a wide range of AI/ML and systems domains.
• Use advanced sourcing methods across LinkedIn and GitHub engineering communities, open-source projects, conferences, and expert networks.
• Build and maintain long-term pipelines of senior engineers for current and future strategic roles.
• Provide hiring teams with regular funnel analytics, insights, and forecasts.
• Craft tailored communication for senior and niche candidates.
• Build trust, communicate value, and represent Nebius’s mission, technical challenges, and engineering culture.
• Conduct initial calls to evaluate technical depth, hands-on experience with modern AI and systems technologies, and overall fit.
• Work directly with engineering and research managers to understand role requirements in detail and shape effective hiring strategies.
• Monitor global trends in LLM research, AI infrastructure, inference efficiency, model deployment, and GPU availability.

Senior Tech Recruiter, ML, LLM

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