דרושים Solutions Architect Ai Infrastructure ב-אנבידיה ב-ארהב

What you’ll be doing:

• Working with tech giants to develop and demonstrate solutions based on NVIDIA’s groundbreaking software and hardware technologies.

• Partnering with Sales Account Managers and Developer Relations Managers to identify and secure business opportunities for NVIDIA products and solutions.

• Serving as the main technical point of contact for customers engaged in the development of intricate AI infrastructure, while also offering support in understanding performance aspects related to tasks like large scale LLM training and inference.

• Conducting regular technical customer meetings for project/product details, feature discussions, introductions to new technologies, performance advice, and debugging sessions.

• Collaborating with customers to build Proof of Concepts (PoCs) for solutions to address critical business needs and support cloud service integration for NVIDIA technology on hyperscalers.

• Analyzing and developing solutions for customer performance issues for both AI and systems performance.

What we need to see:

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

• 4+ years of engineering(performance/system/solution)experience.

• Hands-on experience building performance benchmarks for data center systems, including large scale AI training and inference.

• Understanding of systems architecture including AI accelerators and networking as it relates to the performance of an overall application.

• Effective engineering program management with the capability of balancing multiple tasks.

• Ability to communicate ideas clearly through documents, presentations, and in external customer-facing environments.

Ways to stand out from the crowd:

• Hands-on experience with Deep Learning frameworks (PyTorch, JAX, etc.), compilers (Triton, XLA, etc.), and NVIDIA libraries (TRTLLM, TensorRT, Nemo, NCCL, RAPIDS, etc.).

• Familiarity with deep learning architectures and the latest LLM developments.

• Background with NVIDIA hardware and software, performance tuning, and error diagnostics.

• Hands-on experience with GPU systems in general including but not limited to performance testing, performance tuning, and benchmarking.

• Experience deploying solutions in cloud environments including AWS, GCP, Azure, or OCI as well as knowledge of DevOps/MLOps technologies such as Docker/containers, Kubernetes, data center deployments, etc. Command line proficiency.

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:

• Design, build, and run cloud infrastructure services in scope to meet our business goals performing integrations, migrations, bringups, updates, and decommissions as necessary.

• Participate in the definition of our internal facing service level objectives and error budgets as part of our overall observability strategy.

• Eliminate toil or automate it where the ROI of building and maintaining automation is worth it.

• Practice sustainable blameless incident prevention and incident response while being a member of an on-call rotation.

• Consult with and provide consultation for peer teams on systems design best practices.

• Participate in a supportive culture of values-driven introspection, communication, and self-organization

What we need to see:

• Proficiency in one or more of the following programming languages: Python or Go

• BS degree in Computer Science or a related technical field involving coding (e.g., physics or mathematics) or equivalent experience.

• 5+ years of relevant experience in infrastructure and fleet management engineering.

• Experience with infrastructure automation and distributed systems design developing tools for running large scale private or public cloud systems at scales requiring fully automated management and under active customer consumption in production.

• A track record demonstrating a mix of initiating your own projects, convincing others to collaborate with you, and collaborating well on projects initiated by others.

• In-depth knowledge in one or more of the following: Linux, Slurm, Kubernetes, Local and Distributed Storage, and Systems Networking.

Ways to stand out from the crowd:

• Demonstrating a systematic problem-solving approach, coupled with clear communication skills and a willingness to take ownership and get results such as experience driving a build / reuse / buy decision.

• Experience working with or developing bare metal as a service (BMaaS) associated systems. For example, vending BMaaS, or Slurm running on containers, or vending Kubernetes clusters. Experience working with or developing multi-cloud infrastructure services. Experience teaching reliability engineering (e.g. SRE) and/or other scale-oriented cloud systems practices to peers and/or other companies (e.g. CRE). Experience in running private or public cloud systems based on one or more of Kubernetes, OpenStack, Docker or Slurm.

• Experience with accelerated compute and communications technologies such BlueField Networking, Infiniband topologies, NVMesh, and/or the NVIDIA Collective Communication Library (NCCL).

• Experience working with a centralized security organization to prioritize and mitigate security risks. Prior experience in a ML/AI focused role or on a team matching specific keywords is welcome but not required.

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.

As a senior manager in our global IT PMO team, you will be accountable for critical infrastructure programs supporting Compute platforms and IT Automation. As a leader of these initiatives, you will drive the operating model, scaling approach and playbooks with delivering programs at scale.

What you'll be doing:

• Lead, mentor, and develop a diverse team of Technical Program Managers, fostering professional growth and a culture of accountability and innovation.

• Serve as a force multiplier across the organization by enabling effective coordination of cross-functional initiatives and managing complex interdependencies.

• Promote collaboration in a fast-paced, dynamic environment while guiding teams through uncertainty with clarity, technical insight, and a results-oriented mindset.

• Establish and maintain best-in-class program management practices to optimize delivery efficiency, mitigate risk, and ensure consistent execution excellence.

• Drive continuous improvement by implementing data-driven feedback mechanisms and leveraging metrics to identify and act on opportunities for optimization.

• Own and manage the Infrastructure program portfolio, ensuring alignment with organizational goals, strategic priorities, and resource capacity.

• Lead quarterly portfolio planning sessions to align stakeholders on dependencies, risks, and prioritization of initiatives. Deliver clear, data-driven updates to senior stakeholders, tracking progress against key performance indicators and strategic objectives.

• Evaluate and prioritize new program requests based on strategic value, business impact, and available capacity. Monitor and assess portfolio performance, identifying improvement areas and providing actionable recommendations to leadership.

What we need to see:

• Bachelor's Degree in computer science, other related technical field or equivalent experience.

• 12+ overall years of IT experience.

• 7+ years of experience successfully leading technical programs in a fast paced, multifaceted, enterprise environment.

• In depth technical knowledge of IT infrastructure within Automation, platforms, SW development and observability, and Compute Systems such as OpenShift.

• Deep understanding of infrastructure standards and methodologies to optimize for quality and efficiency. Experience with various continuousintegration/deploymentmodels for large organizations will be important, as well as a foresight towards how to adopt and integrate such practices into a very dynamic infrastructure environment.

• Certified Scrum Master or Certified Scrum Trainer certification or equivalent preferred.

• Proven history of continuous improvement to enable higher performingprogram/organizationsand/or teams with improved business and customer outcomes.

• Consistent track record of delivering critical infrastructure builds, while navigating a fast-paced environment with frequent shift in priorities.

• Effective communication skills both written andverbal/presentations.Ability to bridge from high-level objectives to project details and vice-versa.

• Willingness to work with distributed team members across different time zones.

What you'll be doing:

• Building and maintaining infrastructure from first principles needed to deliver TensorRT LLM

• Maintain CI/CD pipelines to automate the build, test, and deployment process and build improvements on the bottlenecks. Managing tools and enabling automations for redundant manual workflows via Github Actions, Gitlab, Terraform, etc

• Enable performing scans and handling of security CVEs for infrastructure components

• Improve the modularity of our build systems using CMake

• Use AI to help build automated triaging workflows

• Extensive collaboration with cross-functional teams to integrate pipelines from deep learning frameworks and components is essential to ensuring seamless deployment and inference of deep learning models on our platform.

What we need to see:

• Masters degree or equivalent experience

• 3+ years of experience in Computer Science, computer architecture, or related field

• Ability to work in a fast-paced, agile team environment

• Excellent Bash, CI/CD, Python programming and software design skills, including debugging, performance analysis, and test design.

• Experience with CMake.

• Background with Security best practices for releasing libraries.

• Experience in administering, monitoring, and deploying systems and services on GitHub and cloud platforms. Support other technical teams in monitoring operating efficiencies of the platform, and responding as needs arise.

• Highly skilled in Kubernetes and Docker/containerd. Automation expert with hands-on skills in frameworks like Ansible & Terraform. Experience in AWS, Azure or GCP

Ways to stand out from the crowd:

• Experience contributing to a large open-source deep learning community - use of GitHub, bug tracking, branching and merging code, OSS licensing issues handling patches, etc.

• Experience in defining and leading the DevOps strategy (design patterns, reliability and scaling) for a team or organization.

• Experience driving efficiencies in software architecture, creating metrics, implementing infrastructure as code and other automation improvements.

• Deep understanding of test automation infrastructure, framework and test analysis.

• Excellent problem solving abilities spanning multiple software (storage systems, kernels and containers) as well as collaborating within an agile team environment to prioritize deep learning-specific features and capabilities within Triton Inference Server, employing advanced troubleshooting and debugging techniques to resolve complex technical issues.

What you’ll be doing:

• Collaborating with business development in guiding the customer through the solution adoption process for our Metropolis, Isaac and IGX AI SW platforms, GPU Computing and IGX/Jetson, being responsible for the technical relationship and assisting customers in building creative solutions based on NVIDIA

• Be an industry leader with vision on integrating NVIDIA technology into intelligent machines’ architectures

• You will engage with customers to develop a keen understanding of their goals, vision and plans, as well as technical needs – and help to define and deliver high-value solutions that meet these needs

• Train customers on the adoption of our AI platforms, develop and optimize proof of concepts using the Nvidia robotics and Metropolis platforms as well as the Jetson/IGX SDKs

• Establish positive relationships and communication channels with internal teams

What we need to see:

• BS or MS in Electrical Engineering or Computer Science or equivalent experience

• 8+ years of work-related experience in a high-tech electronics industry in a similar role as a systems or solution architect

• AI practitioner experience

• C, C++, and Python coding

• Strong time-management and organization skills for coordinating multiple initiatives, priorities, and implementations of new technology and products into very complex projects

Ways to stand out from the crowd:

• NVIDIA GPU development experience

• Experience with Omniverse, ISAAC and Metropolis

• Experience with generative AI on Jetson or IGX, RIVA, VSS