דרושים Principal Infrastructure Sre - Compute ב-אנבידיה ב-ארהב

You will collaborate closely with researchers to design and scale agents - enabling them to reason, plan, call tools and code just like human engineers. You will work on building and maintaining the core infrastructure for deploying and running these agents in production, powering all our agentic tools and applications and ensuring their seamless and efficient performance. If you're passionate about the latest research and cutting-edge technologies shaping generative AI, this role and team offer an exciting opportunity to be at the forefront of innovation.

What you'll be doing:

• Working with NVIDIA AI Native customers on data center GPU server and networking infrastructure deployments.

• Guiding customer discussions on network topologies, compute/storage, and supporting the bring-up ofserver/network/clusterdeployments.

• Identifying new project opportunities for NVIDIA products and technology solutions in data center and AI applications.

• Conducting regular technical meetings with customers as a trusted advisor, discussing product roadmaps, cluster debugging, and new technology introductions.

• Building custom demonstrations and proofs of concept to address critical business needs.

• Analyzing and debugging compute/network performance issues.

What we need to see:

• BS/MS/PhD in Electrical/Computer Engineering, Computer Science, Physics, or related fields, or equivalent experience.

• 5+ years of experience in Solution Engineering or similar roles.

• System-level understanding of server architecture, NICs, Linux, system software, and kernel drivers.

• Practical knowledge of networking - switching & routing for Ethernet/Infiniband, and data center infrastructure (power/cooling).

• Familiarity with DevOps/MLOps technologies such as Docker/containers and Kubernetes.

• Effective time management and ability to balance multiple tasks.

• Excellent communication skills for articulating ideas and code clearly through documents and presentations.

Ways to stand out from the crowd:

• External customer-facing skills and experience.

• Experience with the bring-up and deployment of large clusters.

• Proficiency in systems engineering, coding, and debugging, including C/C++, Linux kernel, and drivers.

• Hands-on experience with NVIDIA systems/SDKs (e.g., CUDA), NVIDIA networking technologies (e.g., DPU or equivalent experience, RoCE, InfiniBand), and/or ARM CPU solutions.

• Familiarity with virtualization technology concepts.

As part of the NVIDIA Solutions Architecture team, you will navigate uncharted waters and gray space to drive successful market adoption by balancing strategic alignment, data-driven analysis, and tactical execution across engineering, product, and sales teams. You will serve as a critical liaison product strategy and large-scale customer deployment.

What you’ll be doing:

• Lead the end-to-end execution for key Hyperscalers customers to optimally and rapidly go-to-market at scale with NVIDIA data center products (e.g., GB200).

• Partner with Hyperscalers Product Customer Lead to understand strategy, define metrics, ensure alignment.

• Data-Driven Execution: Collect, maintain, and analyze sophisticated data trends to assess the product's market health, identify themes, challenges, and opportunities, and guide the customer to resolution of technical roadblocks.

• Problem Solving & Navigation: Navigate complex issues effectively, embodying a productive leader who balances short-term unblocks with long-term process and product improvements.

• Executive Communication: Deliver concise, direct executive-level updates and regular status communications to multi-functional leadership on priorities, progress, and vital actions.

• Process Improvement: Integrate insights from deployment challenges and customer feedback into future developments for processes and products through close partnership with Product and Engineering teams.

What we need to see:

• BS/MS/PhD in Electrical/Computer Engineering, Computer Science, Physics, or other Engineering fields or equivalent experience.

• 8+ years of combined experience in Solutions Architecture, Technical Program Management, Product Management, System Reliability Engineer or other complex multi-functional roles.

• Proven track record to lead and influence without direct authority across technical and business functions.

• Proven analytical skills with experience in establishing benchmarks, collecting/analyzing intricate data, and redefining data into strategic themes, action items, and executive summaries.

• Skilled in reviewing logs and deployment data, and aiding customers in resolving technical concerns (e.g., identifying performance issues associated with AI/ML and system architecture).

Ways to stand out from the crowd:

• Lead multi-functional teams and influence interested parties to address challenges in customer datacenter deployments, ensuring cluster health and performance at scale.

• Established track record of driving a product from the pilot phase to at-scale deployment in a data center environment.

• Hands-on experience with NVIDIA hardware (e.g., H100, GB200) and software libraries, with an understanding of performance tuning and error diagnostics.

• Knowledge of DevOps/MLOps technologies such as Docker/containers and Kubernetes, and their relationship to data center deployments.

• Confirmed capacity to align, adopt, and disseminate insights among various internal teams (e.g., collaborating with other program leads).

What you'll be doing:

• Path-find technical innovations in Quantum Error Correction and Fault Tolerance, working with multi-functional teams in Product, Engineering, and Applied Research

• Develop novel approaches to quantum error correction codes and their logical operations, including methods for implementation and logical operation synthesis

• Research and co-design improved methods to achieve fault tolerance, such as techniques for logical operations, concatenation, synthesis, distillation, cultivation, or others

• Collaborate with internal teams and external partners on developing technology components to enable a fault-tolerant software stack integrated with quantum hardware

• Adopt a culture of collaboration, rapid innovation, technical depth, and creative problem solving

What we need to see:

• Masters degree in Physics, Computer Science, Chemistry, Applied Mathematics, or related engineering field or equivalent experience (Ph.D. preferred)

• Extensive background in Quantum Information Science with 12+ overall years of experience in the Quantum Computing industry

• A demonstrated ability to deliver high impact value in quantum error correction and fault tolerance

Ways to stand out from the crowd:

• Hands-on experience in scientific computing, high-performance computing, applied machine learning, or deep learning

• Experience with co-design of quantum error correction with quantum hardware or quantum applications

• Experience with CUDA and NVIDIA GPUs

• Passion to drive technology innovations into NVIDIA software and hardware products to support Quantum Computing

What you'll be doing:

• Define and drive architecture for complex, high-volume GPU products, ensuring they meet our ambitious performance and scalability goals.

• Perform and guide power and performance evaluation, trade-off assessments, and architectural modeling to identify optimal chip, package and system construction.

• Lead improvements in architecture, methodology and tools to improve the scalability of our system, collaborating closely with cross-functional engineering teams.

• Specify and optimize SoC subsystems such as memory architecture, test infrastructure and power management.

• Collaborate with RTL, verification, physical design, firmware, and software teams to successfully implement and integrate system components.

• Produce high-quality technical documentation of SoC architecture, specifications, and development trade-offs.

• Provide technical leadership and mentorship to junior architects and engineers, encouraging a culture of excellence and innovation.

What we need to see:

• Over 15 years in SoC architecture development or similar technical leadership roles.

• Proven track record of defining and delivering multiple high-volume SoC systems (such as CPU, GPU, modem, networking or similar).

• Proficiency in evaluating power/performance and architectural modeling in high-level programming languages.

• Strong understanding of SoC system fundamentals, including memory hierarchy, coherency, clocking, power domains, boot and reset, test, and debug methodologies.

• Hands-on experience with silicon bring-up, debug and tuning.

• Excellent interpersonal, leadership, and collaboration skills, with the ability to influence across organizations.

• Outstanding documentation, written, and verbal communication skills.

• Master's degree (or equivalent experience) in a relevant subject area: Computer Science, Electrical Engineering or Computer Engineering

Ways to stand out from the crowd:

• Experience with GPU or AI accelerator architecture, including platform aspects, off-chip I/O technologies, and networked multi-GPU systems

• Knowledgeable in modern packaging technologies, and their costs and benefits

• Knowledgeable in AI workload characteristics

• Outstanding analytical and problem-solving skills with a focus on optimizing performance, power, area, and complexity.

What You'll Be Doing:

• Strategic Leadership: define and own the global go-to-market strategy for the DGX platform, ensuring alignment with long-term business goals and the broader NVIDIA AI portfolio. Continue to establish the DGX platform as the reference build for accelerated infrastructure and model go-to-market for partners, defining messaging and positioning, planning and overseeing complex keynote-level product launches and ongoing product representation.

• Team Management & Mentorship: manage, mentor, and develop a team of product marketers, helping them navigate complex organizational challenges and elevate their strategic thinking. Build and scale the team to support launch strategy, field and channel enablement, ecosystem teamwork, and repeatable messaging frameworks, while developing talent and sustaining organizational alignment.

• Cross-functional Alignment & Ecosystem: serve as the primary product marketing voice for the DGX platform, collaborating across product, campaign, field, and partner teams to align on positioning, resolve messaging conflicts, and oversee product launches. You will define go-to-market strategies for partners to promote growth and ensure consistent representation across the ecosystem.

• Expert Execution: guide the final quality for critical launches and high-stakes deliverables, diving in hands-on when vital to resolve complex positioning issues and unblock your team on difficult cross-functional problems.

What We Need To See:

• 12+ overall years of relevant experience in product marketing, product management, or a related field within enterprise technology or AI infrastructure.

• 5+ years Direct people management experience, with a proven track record of hiring and developing high-performing teams.

• Proficiency in Product Marketing: deep expertise in positioning, messaging, asset creation, and competitive analysis with a passion for transferring this knowledge and empowering a team to master these skills.

• Technical Proficiency: ability to understand complex AI system architectures and translate them into compelling business value.

• Strategic Presence: demonstrated ability to influence senior stakeholders (VPs, Directors), negotiate effectively, and drive consensus across matrixed organizations.

• Bachelor’s degree in Engineering, Computer Science, Marketing, or equivalent experience.

Ways To Stand Out From The Crowd:

• Deep understanding of NVIDIA AI infrastructure, the NVIDIA DGX platform, and the enterprise AI ecosystem.

• A proven ability to encourage and elevate high-performing teams through subject matter expertise and strategic vision.

• A portfolio of high-impact content.

What you'll be doing:

• Act as the subject matter expert (SME) for material management processes supporting data center infrastructure hardware across its full lifecycle.

• Be responsible for the planning and execution of operational hardware sparing strategies to ensure availability and minimal downtime.

• Own the end-of-life (EOL) management process for infrastructure hardware, including decommission planning and material disposition.

• Ensure inventory accuracy through ongoing audits, reconciliation processes, and alignment with data center operational needs.

• Apply ABC inventory classification methodology to prioritize and optimize stock levels based on usage, cost, and criticality.

• Maintain and improve material planning models to support forecasting and capacity planning initiatives.

• Analyze data trends to drive continuous improvements in inventory optimization, cost control, and operational efficiency.

What we need to see:

• 12+ years of experience in material management, inventory operations, or hardware lifecycle support within data center infrastructure, manufacturing, or supply chain environment.

• Solid grasp of data center hardware components (servers, networking, storage, etc.) and their lifecycle (deployment, sparing, EOL).

• Demonstrable experience with inventory control practices, including ABC classification, stock audits, and accuracy initiatives.

• Excellent organizational and documentation skills; attention to detail is a must.

• Bachelor’s degree in Supply Chain Management, Operations, Logistics, Information Technology, or related field; or equivalent experience.