• Manage account and partner responsibilities for selected (Global Major) accounts in assigned territory • Provide the optimum combination of hardware, software, and services to meet complex customer needs • Play a role in the development of the bid, proposal, and presentation of the solution to the prospect • Provide specific solutions/technology/product/technical and sales support for accounts in assigned territory • Deliver technical presentations to customers, partners, and potential prospects • Manage channel partners to help drive business and deliver demand generation events • Develop account relationships over time to continue to deliver advice to the customer and identify additional opportunities; maintain and manage a sales pipeline and forecasts against regional goals

Role Description Nebius is looking for an entrepreneurial, strategic, and partnership-focused professional to join our global startup team as a Venture Ecosystem Lead. In this role, you’ll take ownership of growing and managing our U.S. startup pipeline by developing strong relationships with leading venture capital firms, accelerators, and startup communities. You’ll focus on driving adoption of our established startup program by sourcing high-potential AI startups, co-creating value-added initiatives with partners, and delivering impactful ecosystem activations. You’ll be a strategic thinker and doer—comfortable managing complex partnerships, growing the deal pipeline, and delivering exceptional experiences that deepen Nebius’ role as the cloud partner of choice for AI-native startups in the U.S. You are welcome to work remotely from the United States (NYC preferred). Responsibilities - Develop and Manage Venture Capital Partnerships - Build and maintain strong relationships with leading U.S. venture capital firms, accelerators, and key startup ecosystem partners. - Act as a trusted Nebius representative, growing visibility and influence in the VC and startup ecosystem. - Drive and Grow Startup Pipeline - Source, qualify, and onboard high-potential AI startups into Nebius’ established startup program. - Collaborate with sales and marketing teams to ensure clear tracking, strong engagement, and effective conversion into long-term Nebius users. - Create and Deliver Value-Added Initiatives - Design and execute tailored partner initiatives, joint campaigns, and enablement resources. - Develop compelling GTM materials such as case studies and playbooks to support adoption and success. - Measure and Optimize Partnership Success - Own and track KPIs including lead generation, startup acquisition, activation rates, and revenue contribution. - Use data and feedback to evaluate impact, identify opportunities, and optimize strategies. - Collaborate Across Teams - Partner with internal stakeholders—including marketing, sales, product, and solutions architecture—to align goals and ensure seamless execution. - Champion the voice of the U.S. startup and VC community within Nebius. Qualifications - Minimum 7+ years of professional experience in strategic partnerships, business development, or sales & GTM, with at least 5 years working in the startup or venture ecosystem. - Deep understanding of VC and startup dynamics, investment models, and growth strategies. - Proven ability to drive qualified pipeline growth and deliver measurable business impact through partnerships. - Excellent organizational, communication, and presentation skills. - Ability to work independently and collaboratively in a fast-paced, cross-functional environment. - Familiarity with the AI and cloud computing landscape, with the ability to learn new technologies quickly. - Genuine passion for the startup ecosystem, with consistent participation in the VC or technology events and conferences. - Experience using CRM tools for pipeline management, internal communication, and workflow automation. Requirements - 5+ years of experience working in a VC firm, accelerator, as a startup founder, or as an early team member of a venture-backed AI startup. - Established, high-trust network within the U.S. venture capital ecosystem. - Experience in technology partnerships or selling AI/cloud solutions. - Strong understanding of AI infrastructure, cloud solutions, and the needs of AI/ML startups. Benefits - Health insurance: 100% company-paid medical, dental, and vision coverage for employees and families. - 401(k) plan: Up to 4% company match with immediate vesting. - Parental leave: 20 weeks paid for primary caregivers, 12 weeks for secondary caregivers. - Remote work reimbursement: Up to $85/month for mobile and internet. - Disability & life insurance: Company-paid short-term, long-term and life insurance coverage. - Competitive salaries, ranging from $200k - $250k OTE + equity based on your experience. - Career growth and learning opportunities. - Flexibility and work-life balance. - Collaborative and innovative culture. - Opportunity to work on impactful AI projects. - International environment and talented teams.

• Serve as a primary system owner for finance and manufacturing business systems, including Coupa, Microsoft Business Central (BC), Graphite, Arena, Brex, and SimpleLegal • Perform hands-on system administration, including user access, roles, permissions, configuration, and master data management • Gather, document, and translate business requirements into system configurations, enhancements, and process improvements • Identify opportunities to improve system efficiency, data accuracy, automation, and user experience, with a focus on manufacturing and finance workflows • Support core manufacturing data and processes across PLM, ERP, and MES systems, including parts, BOMs, revisions, lifecycle states, routings, work orders, shop floor execution, inventory, WIP, and production transactions • Ensure accurate and timely flow of manufacturing data between Arena, Business Central, and MES platforms • Partner with Manufacturing and Supply Chain teams to support production operations, engineering change management, and scale-up activities • Own and support integrations across key enterprise systems, including Graphite ↔ Business Central, Coupa ↔ Business Central, SimpleLegal → Coupa, Arena → Business Central, and Business Central → MES • Troubleshoot integration issues, ensure data integrity, and coordinate with technical teams to resolve defects • Document data flows, dependencies, controls, and integration processes across systems • Partner closely with Procurement, Legal, Finance, and Manufacturing teams to understand operational requirements and identify opportunities for improvement • Act as a liaison between business stakeholders and technical teams to ensure successful delivery of system enhancements and process changes • Support system-related initiatives, including implementations, upgrades, testing, and process improvements • Ensure systems and integrations align with accounting principles, financial controls, and compliance requirements • Validate transactional data across systems to maintain consistency, accuracy, and compliance • Support audits, reporting, reconciliations, and data governance activities

Role Description As a Member of Technical Staff, System Modeling (Dynamic Systems Simulation), you will be part of a hands-on R&D team building simulation frameworks that enable testing and rapid iteration across all layers of unconventional physics-based computing systems for machine learning workloads. “Extreme co-design” is our guiding principle. System Modeling is a multi-disciplinary effort, and the team we’re building reflects that. The role involves: - Development of physics-based system models - GPU-accelerated ML system simulations - Cross-layer system integration You don’t need to be an expert in all of these, but you have to be very strong in at least one, and solid in the rest. You will be responsible for developing high-performance PyTorch components that model complex, time-varying dynamic systems. Your work will directly enable next-generation AI architectures, requiring a holistic approach involving everything from high-level neural network design down to the fundamental differential equations that govern system behavior. Qualifications - MS/PhD in a quantitative field (AI/ML, Computer Science, Physics, Electrical Engineering, Applied Math), or BS with substantial, clear evidence of equivalent research/engineering depth. - Dynamical systems simulation knowledge - Advanced Neural Modeling (PyTorch): - Deep proficiency in PyTorch, specifically in building custom autograd functions and integrating numerical solvers (e.g., Neural ODEs) to represent dynamic processes. - Dynamics & Differential Equations: - A strong theoretical and practical grasp of linear and non-linear dynamics, state-space representations, and solving $dx/dt = f(x, u, t)$ within a machine learning context. - Stochastic Processes & Noise: - Understanding how to model and mitigate noise in real-world systems, including experience with stochastic differential equations (SDEs) or Bayesian filtering. - Modeling & Simulation (M&S): - Proven industry experience building high-fidelity simulations that balance computational efficiency with physical accuracy. - Systems Engineering (Analog/Digital): - Familiarity with hardware-level concepts like circuit dynamics, signal processing, or transfer functions is highly desirable to help ground our digital models in physical reality. - ML and systems fluency: - Solid understanding of modern AI/ML architectures and training/inference workflows. - Strong experience implementing and debugging ML models in PyTorch (preferred) or similar, with practical experience profiling, optimizing, and stabilizing non-trivial large-scale ML systems. Requirements - Strong Python engineering skills: modular design, testing, packaging, CI. - Experience with PyTorch internals: autograd, custom modules, low-level ops; familiarity with torch.compile or similar graph capture/compile flows. - Experience with CUDA, Triton, or other GPU programming approaches (writing custom kernels, understanding memory hierarchy, basic performance tuning). - Comfort with at least some of: JAX, NumPy, TensorFlow, Modal, HPC patterns (MPI, NCCL, distributed training), SciPy. - Demonstrated ability to reason across multiple layers of the stack: algorithm, software, runtime, hardware. - Able to connect model architecture choices to system performance implications: memory bandwidth, communication patterns, latency, energy, and numerical issues. - Experience applying at least some efficiency techniques (quantization, sparsity, pruning, distillation, kernel fusion, etc.). Benefits - A comprehensive package including best-in-class health benefits - 401k matching - Truly unlimited PTO - Complimentary meals when working from our Palo Alto office