דרושים Director Engineering - Power Performance Software ב-אנבידיה ב-ארהב

What you'll be doing:

• Onboard new repair partners and manage day-to-day repair operations across our sites, ensuring all facilities achieve turnaround time and quality targets.

• Lead daily operational reviews with repair partners to track key operational metrics, resolve bottlenecks, and enforce accountability for on-time delivery and repair commitments.

• Function as the key intermediary between repair partners and NVIDIA internal teams — Engineering, Quality, Procurement, Logistics, and Planning — to set shared goals and overcome barriers to meeting targets.

• Drive continuous improvement in repair processes, capacity utilization, yield, and quality through structured root-cause and corrective-action initiatives.

• Coordinate repair commit performance (planned vs. actual), monitoring metrics such as on-time completion rate, FA/bonepile recovery time, turnaround time, and test yield.

• Evaluate capital expenditures and repair expenses, and hold quarterly business meetings with repair collaborators.

• Partner with Engineering and Quality to implement repair process controls, engineering change management, and compliance audits.

• Work with Planning and Procurement to ensure supply chain readiness for new service offerings and ongoing repair builds.

• Champion operational excellence by ensuring sites meet quality and delivery commitments, improving metrics.

What we need to see:

• Bachelor’s degree in Engineering, Operations, Supply Chain, or equivalent experience.

• 15+ overall years of hands-on operations experience managing technology repair, refurbishment, or production environments.

• 8+ years ofmanagement/leadershipexperience in reverse logistics or repair operations, including managing multiple sites and vendors (domestic and international).

• Established record of managing daily factory performance, tracking critical metrics, and ensuring vendor accountability.

• Strong understanding of OEM server, PCBA, and system test processes.

• Experience implementing process improvements, capacity planning, and inventory control systems at repair or manufacturing facilities.

• Demonstrated ability to lead cross-functional teams (Engineering, Quality, Planning, Procurement) and deliver measurable performance gains.

• Data-driven decision maker with excellent problem-solving, communication, and vendor management skills.

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.

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:

• Develop and test sample applications for chemistry and materials discovery using artificial intelligence.

• Help develop AI first workflows using NVIDIA technology and popular deep learning frameworks.

• Create clear, practical examples and documentation for developers and researchers.

What we need to see:

• Pursuing a PhD in Chemistry, Materials Science, Computer Science, or a related field.

• Familiarity with AI/ML concepts and experience with at least one deep learning framework (e.g., PyTorch, TensorFlow).

• Basic understanding of chemistry or materials science principles.

Ways to stand out from the crowd:

• Experience with GPU programming or CUDA and machine learning frameworks such as PyTorch.

• Contributions to open-source projects related to AI or scientific computing.

• Coursework or projects involving AI for scientific applications.

You will also be eligible for Intern

NVIDIA has been transforming computer graphics, PC gaming, and accelerated computing for more than 25 years. It’s a unique legacy of innovation that’s fueled by incredible technology—and amazing people.

What you'll be doing:

You will invent a full range of items and compositions that connect with significant themes, narratives, and product launches. From concept to production, you'll define the art direction for our global employee Gear Store and company merchandise, including the aesthetic, color, materials, and overall style. Work with the merchandise buyer and operations lead to establish roadmaps for our product collections. Direct the user experience and development of our on-site store, event pop-ups, and website.

What we need to see:

• A portfolio showcasing excellence in crafting purposeful, beautiful designs for merchandise—apparel, soft and hard goods. Actual examples of your hands-on illustration and design work, including production.

• A deep knowledge bank of materials, production processes, decoration techniques, complexities, and caveats.

• Proven examples demonstrating your ability to art direct, invent, construct, and conceptualize ideas and innovative creative concepts, particularly relating to abstract and technicalsubjects—transformingideas into sought-after gear.

• Evidence of how you stay on top of the latest trends in the apparel and merchandise space, tech industry trends and technologies— and embrace change.

• Demonstration of the fundamental principles of art direction, graphic composition for brand, illustration, typography, video, photography, and even 3D.

• Your passion to take intent and direction from your peers and leaders and apply your art direction skills to build a vision, iterate quickly, revise, and produce final artwork.

• 10+ years of proven experience working with established brands, building or extending apparel or merchandise collections, collaborating with senior executive level leadership teams.

• Proficiency in Microsoft Office and/or Google Suite applications, tracking your work in project tracking tools such as Workfront.

• A BFA, BS, or MFA in Graphic Development, Illustration, Fashion Composition, or equivalent field is required (or equivalent experience).

Ways to stand out from the crowd:

• Are you curious and passionate about technology, design, and the rapidly evolving AI landscape? Show us you embrace AI, are an AI expert, and have successfully integrated AI tools into to your creative process or workflow.

• Have experience working at a global apparel or premium lifestyle brand? Show us how you understood and integrated established brand systems and technologies into coveted items.

• Do you have hands-on skills in illustration, infographics, 3D, motion graphics, video, photography or storyboarding? Can you sketch, or develop retail displays? Share your creative passions with us!

What we need to see:

• MS or PhD degree in Electrical Engineering, Computer Science or equivalent experience.

• Minimum of 8 years relevant experience

• We require proven theoretical knowledge of communication systems, communication theory, linear algebra, detection and estimation theory, baseband signal processing algorithms, and channel coding

• We seek deep expertise in LTE/5G NR L1 (PHY) and L2 (MAC-scheduler) algorithms design and optimizations

• Experience with wireless algorithm performance characterization and analysis

• Wireless base station design, development, and commercialization experience

• Experience building system models with Matlab, C/C++ and/or Python for algorithm design and link-level simulation

• Solid knowledge of 3GPP 5G NR standard

• Strategic context of Telecom Industry and Wireless technology evolution

Ways to stand out from the crowds:

• Research experience in AI/ML and its applications to wireless applications

• Demonstrated experience in software development for commercial RAN products

• Knowledge of SIMD computing architecture

• Background of GPU or CUDA programming

• Knowledge of Wireless Protocols and E2E Deployment Architecture

What you’ll be doing:

• Contribute features to vLLM that empower the newest models with the latest NVIDIA GPU hardware features; profile and optimize the inference framework (vLLM) with methods like speculative decoding,data/tensor/expert/pipeline-parallelism,prefill-decode disaggregation.

• Develop, optimize, and benchmark GPU kernels (hand-tuned and compiler-generated) using techniques such as fusion, autotuning, and memory/layout optimization; build and extend high-level DSLs and compiler infrastructure to boost kernel developer productivity while approaching peak hardware utilization.

• Define and build inference benchmarking methodologies and tools; contribute both new benchmark and NVIDIA’s submissions to the industry-leading MLPerf Inference benchmarking suite.

• Architect the scheduling and orchestration of containerized large-scale inference deployments on GPU clusters across clouds.

• Conduct and publish original research that pushes the pareto frontier for the field of ML Systems; survey recent publications and find a way to integrate research ideas and prototypes into NVIDIA’s software products.

What we need to see:

• Bachelor’s degree (or equivalent expeience) in Computer Science (CS), Computer Engineering (CE) or Software Engineering (SE) with 7+ years of experience; alternatively, Master’s degree in CS/CE/SE with 5+ years of experience; or PhD degree with the thesis and top-tier publications in ML Systems, GPU architecture, or high-performance computing.

• Strong programming skills in Python and C/C++; experience with Go or Rust is a plus; solid CS fundamentals: algorithms & data structures, operating systems, computer architecture, parallel programming, distributed systems, deep learning theories.

• Knowledgeable and passionate about performance engineering in ML frameworks (e.g., PyTorch) and inference engines (e.g., vLLM and SGLang).

• Familiarity with GPU programming and performance: CUDA, memory hierarchy, streams, NCCL; proficiency with profiling/debug tools (e.g., Nsight Systems/Compute).

• Experience with containers and orchestration (Docker, Kubernetes, Slurm); familiarity with Linux namespaces and cgroups.

• Excellent debugging, problem-solving, and communication skills; ability to excel in a fast-paced, multi-functional setting.

Ways to stand out from the crowd

• Experience building and optimizing LLM inference engines (e.g., vLLM, SGLang).

• Hands-on work with ML compilers and DSLs (e.g., Triton,TorchDynamo/Inductor,MLIR/LLVM, XLA), GPU libraries (e.g., CUTLASS) and features (e.g., CUDA Graph, Tensor Cores).

• Experience contributing tocontainerization/virtualizationtechnologies such ascontainerd/CRI-O/CRIU.

• Experience with cloud platforms (AWS/GCP/Azure), infrastructure as code, CI/CD, and production observability.

• Contributions to open-source projects and/or publications; please include links to GitHub pull requests, published papers and artifacts.