דרושים Solutions Architect Spectrum-x - Dpu/roce-centric ב-אנבידיה ב-United States, Texas

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:

• As a member of the architecture team, you will be responsible for understanding how the GPU sub-system modules interoperate and interact with overall system

• You will architect and plan features in concert with software, hardware, and verification teams across the globe to implement the next iteration of GPUs

• Create functional and performance models, often in C++, along with test plans to validate the features you design

• Actively support post-silicon validation activities

• Constantly learning and growing!

What we need to see:

• BS or MS in compute architecture, Computer Science, or Electrical Engineering (or related degree) or equivalent experience

• 8+ years of experience crafting production code in C or C++

• Course workor industry experience in Computer Architecture, Operation systems, and/or system architecture

Ways to stand out from the crowd:

• Knowledge of Advanced interconnects (PCIe, AXI, nvlink, or similar)

• Experience with scripting languages such as Perl

• Understanding of modern security constructs and/or encryption

• Knowledge of RiscV architecture and microcode development

What you’ll be doing:

• Understand, analyze, profile, and optimize AI training workloads on state-of-the-art hardware and software platforms.

• Guide development of future generations of artificial intelligence accelerators and systems.

• Develop detailed performance models and simulator infrastructure for computing systems accelerating AI training, and implement and evaluate hardware feature proposals.

• Collaborate across the company to guide the direction of machine learning at NVIDIA; spanning teams from hardware to software and research to production.

• Drive HW/SW co-design of NVIDIA’s full deep learning platform stack, from silicon to DL frameworks.

What we need to see:

• PhD in CS, EE or CSEE and 3+ years; or MS (or equivalent experience) and 6+ years of relevant work experience.

• Strong background in computer architecture, with a proven track record of architecting features in shipping high-performance processors.

• Background in artificial intelligence and large language models, in particular training algorithms and workloads.

• Experience analyzing and tuning application performance on state-of-the-art hardware.

• Experience with processor and system-level performance modelling, simulation, and evaluation before silicon exists.

• Programming skills in C++ and Python.

• Familiarity with GPU computing across all layers of the AI stack, from DL frameworks like PyTorch down to CUDA.

What you'll be doing:

• You will be contributing to power estimation models and tools for GPU products and systems like NVIDIA DGX.

• Early GPU & System Architecture exploration with focus on energy efficiency and TCO improvements at GPU and Datacenter level.

• You will help with Performance vs Power Analysis for NVIDIA future product lineup.

• Deploy machine learning techniques to develop highly accurate power and performance models of our GPUs, CPUs, Switches, and platforms.

• Understand the workload characteristics for GenAI/HPC workloads at Datacenter Scale (multi-GPU) to drive new HW/SW features for Perf@Watt improvements.

• Modeling & analysis of cutting-edge technologies like high speed & high-density interconnects.

What we need to see:

• Pursuing a MSEE/MSCE, or equivalent experience related to Power / Performance estimation and optimization techniques.

• Knowledge of energy efficient chip design fundamentals and related tradeoffs.

• Familiarity with low power design techniques such as multi-VT, Clock gating, Power gating, and Dynamic Voltage-Frequency Scaling (DVFS).

• Understanding of processors (GPU is a plus), system-SW architectures, and their performance/power modeling techniques.

• Proficiency with Python and data analysis packages like: Pandas, NumPy, PyTorch.

• Familiarity with performance monitors/simulators used in modern processor architectures.

What you’ll be doing:

• Working with Cloud Service Providers to develop and demonstrate solutions based on NVIDIA’s groundbreaking software and hardware technologies.

• Build and deploy solutions at scale using NVIDIA's AI software on cloud-based GPU platforms.

• Build custom PoCs for solutions that address customer's critical business needs while applying NVIDIA's hardware and software technologies.

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

• Conduct regular technical customer meetings for project/product details, feature discussions, intro to new technologies, and debugging sessions.

• Prepare and deliver technical content to customers including presentations about purpose-built solutions, workshops about NVIDIA products and solutions, etc.

What we need to see:

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

• 7+ years of Solutions Engineering (or similar Sales Engineering roles) experience.

• Established track record of deploying AI/ ML solutions in cloud environments including AWS, GCP, Azure or OCI

• Knowledge of DevOps/MLOps technologies such as Docker/containers, Kubernetes, data center deployments, etc.

• Effective time management and capable of balancing multiple tasks.

• Ability to communicate ideas clearly through documents, presentation, etc.

Ways to stand out from the crowd:

• AWS, GCP, Azure or OCI Professional Solution Architect Certifications

• Hands-on experience with NVIDIA GPUs and SDKs (i.e. CUDA, Triton, TensorRT-LLM, etc.)

• Deep understanding of the full software development lifecycle, including best practices for system design, architectural patterns, and comprehensive testing.

• Solid working knowledge of Python

• System-level experience, specifically GPU-based systems

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.