דרושים Engineering Manager - Rack Scale Ai Systems ב-אנבידיה ב-ארהב

What you will be doing:

• Drive strategic CSP partnerships, collaborate with keyhyperscaleCSPs to align project schedules, priorities, and technical roadmaps for next-generation data center platforms.

• Manage complex technical collaborations proactively, identifying and resolving critical issues before they impact customer deployments.

• Orchestrate internal stakeholder alignment ensuring CSP priorities are reflected across NVIDIA's engineering, product, and business.

• Create comprehensive customer program visibility through executive dashboards, status reports, and metrics tracking that provide real-time insights into CSP project health, risks, and milestone achievement.

• Lead large-scale deployment programs managing multi-rack, hyperscale infrastructure rollouts with complex technical dependencies, timeline coordination, and resource alignment across multiple internal teams.

What we need to see:

• Technical Expertise: Solid understanding of system software design, OS fundamentals, Linux kernel development, and hardware/software interfaces. Experience in GPU-based data center server architectures.

• Program Management: Proven ability to lead software development for rack-scale systems and data center servers, including complex hardware/software integration projects.

• Industry Collaboration: Experience partnering with hyperscalers to drive technical outcomes, manage dependencies, handle escalations, and communicate effectively at the executive level.

• Communication & Leadership: Exceptional ability to translate technical concepts for business stakeholders and align diverse teams toward common goals.

• BS or MS in Computer Engineering, Computer Science, or related field or equivalent experience.

• 8+ years of technical program management experience in HPC or data center server software development.

Ways to stand out from the crowd:

• Prior hands-on technology development experience in out-of-band manageability and observability solutions, system software/Linux kernel driver development, CUDA programming, or LLM/AI framework development.

What you’ll be doing:

• Lead financial planning and analysis for the global Hardware Engineering organization, driving forecasting, budgeting, and investment optimization.

• Oversee engineering inventory management, including forecasting, reserve analysis, and excess material reviews.

• Manage global engineering lab investments by planning equipment purchases based on company roadmaps and partnering closely with engineering leaders to ensure alignment with development priorities.

• Develop and maintain dynamic financial reporting frameworks covering budget, forecast, and variance analytics that improve visibility and decision-making.

• Leverage Artificial Intelligence and automation tools (such as Claude, Perplexity, Copilot, Databricks, Alteryx, and Power BI) to build scalable data models, dashboards, and analytical reports that generate actionable business insights.

• Drive process improvements that enhance accuracy, efficiency, and transparency across engineering finance operations.

What we need to see:

• Bachelor’s degree in Finance, Data Science, Engineering, or a related field (or equivalent experience); MBA or advanced degree preferred.

• 5+ years of experience in financial planning and analysis, preferably within a global high-tech or manufacturing organization.

• Proven expertise in data analytics and financial modeling, including proficiency in tools and programming languages such as Python, SQL, or similar.

• Strong understanding of accounting principles and experience with financial ERP systems (SAP experience a plus).

• Exceptional analytical, problem-solving, and business partnership skills with the ability to translate complex data into clear, actionable insights.

Ways to stand out from the crowd:

• Semiconductor and/or manufacturing experience in tech.

• Genuine curiosity in STEM and eagerness to learn new things.

• Strong understanding of industry technology and market dynamics in areas directly related to NVIDIA’s products, research and development.

What you’ll be doing:

• Act as a technical advisor, collaborating with partner engineering teams on architecture, integration, and code for Isaac Sim, Isaac Lab, and AI-enabled robotics solutions.

• Build and maintain deep expertise in NVIDIA robotics SDKs, with a focus on simulation and robot learning.

• Track emerging trends in the robotics ecosystem to identify new opportunities.

• Co-design and deliver advanced robotic solutions with partners—defining objectives, architecture, milestones, and implementation plans.

• Create technical enablement resources such as sample code, reference architectures, integration guides, and workshops.

• Work closely with partner engineering leaders and decision-makers to identify challenges, recommend solutions, and drive adoption of NVIDIA robotic technology.

• Represent partner needs internally, providing feedback to NVIDIA’s product and engineering teams to influence future roadmaps.

• Support product launches and go-to-market activities with technical validation, demos, and customer-facing materials.

What we need to see:

• 10+ years in the technology industry, with at least 5 years in hands-on software development or engineering.

• Bachelor’s or Master’s in Computer Science, Engineering, or a related technical field—or equivalent experience.

• Whole software development lifecycle experience—from requirements and design to testing, integration, and support.

• Technical background in at least one of: robot foundation models, simulation, synthetic data, robot perception, reinforcement learning, or imitation learning.

• Expertise with robotics simulation tools (e.g., Gazebo, MuJoCo, Isaac Sim, Robot Studio).

• Experience leading technical workshops, code reviews, and architectural design sessions.

• Strong communication skills for technical and executive audiences.

• Ability to structure and deliver complex technical engagements.

Ways to stand out from the crowd:

• Experience with NVIDIA tools and libraries (CUDA-X, Isaac Sim, OpenUSD, Cosmos).

• Recent hands-on experience with robot simulation tools.

• Knowledge of AIOps, cloud-native technologies, Kubernetes, Docker, and monitoring tools.

• Proven success growing developer ecosystems through technical enablement.

What You'll Be Doing:

• Working as a key member of our cloud solutions team, you will be the go-to technical expert on NVIDIA's products, helping our clients architect and optimize GPU solutions for AI services.

• Collaborating directly with engineering teams to secure design wins, address challenges, usher projects into production, and offer support through the project's lifecycle.

• Acting as a trusted advisor to our clients, while developing reference architectures and best practices for running Microsoft AI workloads on NVIDIA infrastructure.

What We Need To See:

• 4+ years of experience in cloud computing and/or large-scale AI systems.

• A BS in EE, CS, Math, or Physics, or equivalent experience.

• A proven understanding of cloud computing and large-scale computing systems.

• Proficiency in Python, C, or C++ and experience with AI frameworks like Pytorch or TensorFlow.

• Passion for machine learning and AI, and the drive to continually learn and apply new technologies.

• Excellent interpersonal skills, including the ability to explain complex technical topics to non-experts.

Ways To Stand Out From The Crowd:

• Recent projects or contributions (for example, on GitHub) related to large language models and transformer architectures.

• Knowledge of Azure cloud and AzureML services.

• Experience with CUDA programming and optimization.

• Familiarity with NVIDIA networking technologies such as Infiniband.

• Proficiency in Linux, Windows Subsystem for Linux, and Windows.

What you’ll be doing:

• Lead communications strategy and execution for quantum computing, computer-aided engineering (CAE), simulation and modeling technologies

• Collaborate with business leaders, marketing leads and industry partners to develop and tell compelling stories

• Develop key messages that resonate with external audiences

• Pitch and manage stories with reporters to secure impactful press coverage

• Nurture strong long-term relations with general and technology media

What we need to see:

• 8+ years of PR/comms experience at leading tech companies/agencies and a bachelor’s degree or equivalent experience

• Experience leading media relations strategy and execution in a high-stakes environment

• Outstanding communication skills, including professional writing abilities and verbal communication

• Ability to uplevel technical messages into compelling narratives that are understandable to audiences of all types

• Demonstrate an eagerness to go above and beyond, seek out challenges, and anticipate needs before they arise

• Able to think outside of launches and announcements to keep PR momentum going through proactive opportunities

• Highly detail-oriented with outstanding project-management skills

• Proven ability to generate great media coverage for technology

• Creative, collaborative, and organized, with a knack for balancing multiple projects

Ways to stand out from the crowd:

• PR experience in AI, enterprise, quantum computing or CAE

• Voracious appetite for AI, enterprise, quantum computing and CAE news

• Strong relationships with technology reporters in the data center, quantum computing and CAE space

What you'll be doing:

• Design, build and optimize agentic AI systems for the CUDA ecosystem.

• Co-design agentic system solutions with software, hardware and algorithm teams; influence and adopt new capabilities as they become available.

• Develop reproducible, high-fidelity evaluation frameworks covering performance, quality and developer productivity.

• Collaborate across the AI stack—from hardware throughcompilers/toolchains,kernels/libraries, frameworks, distributed training, andinference/serving—andwith model/agent teams.

What we need to see:

• Bachelor’s degree in Computer Science, Electrical Engineering, or related field (or equivalent experience); MS or PhD preferred.

• 3 years+ industry or academia experience with AI systems development; exposure to building foundational models, agents or orchestration frameworks; hands-on experience with deep learning frameworks and modern inference stacks.

• Strong C/C++ and Python programming skills; solid software engineering fundamentals.

• Experience with GPU programming and performance optimization (CUDA or equivalent).

Ways To Stand Out From The Crowd:

• Strong experience in building/evaluating deep learning models, coding agents and developer tooling.

• Demonstrated ability to optimize and deploy high-performance models, including on resource-constrained platforms.

• Demonstrated ability in GPU performance optimizations, evidenced by benchmark wins or published results.

• Publications or open-source leadership in deep learning, multi-agent systems, reinforcement learning, or AI systems; contributions to widely used repos or standards.

What you’ll be doing:

• Own Initial Power-On and Board Bring-Up: Lead the initial power-on and functional validation of compute trays (CPU, GPU, NIC, storage including NVMe, cooling, etc.) internally and with customers. Ensure all functional requirements are met.

• Form and lead a virtual team across NVIDIA software & firmware teams to ensure subject matter experts are available as needed throughout bringup. Regular reporting on status of bringup to provide visibility and ensure teams across the company are fully activated to help.

• Oversee flashing, updating, and validation of firmware for all server components as per defined architecture. Ensure appropriate validation done for boundary, stress, and regression testing, and confirm telemetry, logging, and hardware management features working as per requirements. Document pain points, bring up failures, recovery flows, and provide actionable feedback to hardware, firmware, and software teams. Ensure usability, firmware/BIOS update coverage, and error reporting for reliable customer installation and operation

• Factory & Manufacturing Support: Support manufacturing flows, firmware updates, and diagnostic procedures. Ensure BOM change signoff and process optimization.

• Debug, Issue Resolution & Customer Support: Lead root cause analysis and resolution of bring-up failures. Collaborate with partners, ODMs, and customers for technical support.

• Documentation & Knowledge Transfer: Own and maintain platform design guides, bring-up checklists, and install instructions. Provide training and enablement for internal and external teams.

• Product Ownership: Drive product life cycles with QA teams, ensuring robust bring up, productization, and delivery.

• Performance Management: Conduct performance evaluations, develop a culture of excellence, and ensure high productivity.

What we need to see:

• 5+ years of relevant experience managing systems/platform software teams, ideally in server bring up, firmware development, or data center solutions.bDeep experience operating successfully in a matrix environment, forming and leading high impact virtual teams spanning multiple disciplines.

• BS, MS, or PhD in EE/CS or related field (or equivalent experience) with 12+ overall years of experience. Strong knowledge of compute tray designs, firmware enablement, and system-level architecture.

• Proven track record of delivering scalable server products and solutions for large scale data centers. ​Experience collaborating with hardware, firmware, manufacturing, diags and QA teams

• Experience with SCM (Git, Perforce) and project management tools (Jira).

• Excellent written and oral communication skills, strong work ethic, and dedication to teamwork.

• Hands-on experience with x86/ARM system architecture and coding (C/C++, Python).

• You are a self-starter who loves to find creative solutions to complicated problems.

• Proven excellence in server architecture, collaborating across teams for delivering server products as per defined Key Performance Indicators (KPIs).

Ways to stand out from the crowd:

• Experience leading bring-up for sophisticated compute architectures like GB200 NVL72.