דרושים Gpu Graphics Performance Architect - Ncg ב-אנבידיה ב-China, Shanghai

What you’ll be doing:

• Be responsible for running test cases to validate NVIDIA GPU Communications Libraries (NCCL, NVSHMEM, UCX, GDRCopy, GPUDirect RDMA etc).

• Be responsible to automate test cases and maintain the automation scripts.

• Collaborate with Developer, PM, marketing, and engineering teams on crafting test plan and implementing validation.

• You will assist in the architecture, crafting and implementing of SWQA test frameworks.

• Be responsible for code coverage improvement and code complexity optimization.

What we need to see:

• BS or higher degree in CS/EE/CE or equivalent experience

• 5+ years of relevant experience

• Seasoned software QA or software testing background; test infrastructure and strong analysis skills

• Be proficient in scripting language (Python, Perl, bash)

• Solid experience with AI development tools for test development and automation

• Knowledge of basic networking concepts

• UNIX/Linux experience is required

• Experiences in C/C++ is required

• Ability to work independently and leadership skillsas well as experience in using quality mindset to drive improvements

• Proficient oral and written English

Ways to stand out from the crowd:

• Experience with CUDA programming and NVIDIA GPUs

• Knowledge of high-performance networks like InfiniBand, RoCE,etc

• Experience with CSPs(AWS, Google Cloud, Oracle Cloud Infrastructure, Microsoft Azure), andHPC cluster,slurm, ansible, etc

• Prior experience with virtualization technologies (KVM, HyperV, VMWARE, OpenStack, Docker, Kubernetes)

• Experience with Deep Learning Frameworks such as PyTorch, TensorFlow, etc

NVIDIA has been redefining computer graphics, PC gaming, and accelerated computing for more than 25 years, driven by exceptional technology and outstanding individuals. Today, we're tapping into the unlimited potential of AI to define the next era of computing, where our GPU acts as the brains of immersive digital worlds and creative applications. As an NVIDIAN, you'll be immersed in a diverse, encouraging environment where everyone is inspired to do their best work.

• Establish and scale NVIDIA's neural graphics organization in China, building research and engineering teams

• Define and implement our neural graphics strategy for China and its integration into NVIDIA's graphics platform

• Build strategic partnerships with China's leading VLM and neural graphics research institutions and talent

• Lead recruitment of exceptional talent in neural rendering, vision-language models, and differentiable programming

• Drive research-to-product pipeline, translating China's VLM innovations into shipping products and platforms globally

• Architect system-level integration of neural graphics technologies across NVIDIA's platform ecosystem

• Represent NVIDIA across the world's graphics and AI research community, establishing thought leadership

• Partner with executive leadership to develop company-wide neural graphics strategy and roadmap

• Degree in Computer Science, Computer Graphics, Machine Learning, or equivalent experience that is outstanding

• 12+ years experience, 6+ years leading teams

• Deep connections in the neural graphics research community

• Proven track record of building organizations and scale teams in fast paced technical domains

• Strong understanding of ML frameworks, VLM architectures, and AI technologies with experience bringing them to production

• Experience defining platform strategies with demonstrated research-to-product transfers and measurable business impact across global markets

• Excellent interpersonal and communication skills to lead across research, product, and executive teams in both Chinese and English

• Established thought leadership in neural graphics, VLMs, or AI-powered rendering with industry recognition

• Experience building successful research-industry partnerships in China's AI ecosystem

• Track record shipping graphics or AI platforms used by developers worldwide

• Conference presentations, publications, or awards in graphics, VLMs, or AI

• Experience establishing new technical organizations or regional presences

What you'll be doing:

• Use internally developed tools and industry standard pre-silicon gate-level and RTL power analysis tools, to help improve product power efficiency.

• Develop and share best practices for performing pre-silicon power analysis, Enhance internal power tools and automate best practices

• Perform comparative power analysis, to spot trends and anomalies, that warrant more scrutiny.

• Interact with architects and RTL designers to help them interpret their power data and identify power bugs; drive them to implement fixes.

• Select and run a wide variety of workloads for power analysis, Collaborate with performance and architecture teams to validate performance of the workloads

• Prototype a new architectural feature in Verilog and analyze power.

What we need to see:

• EE, MS or PhD in related fields, or equivalent experience.

• Basic understanding of concepts of energy consumption, estimation, and low power design.

• Familiarity with Verilog and ASIC design principles, including knowledge of logic cells.

• Good verbal/written English and interpersonal skills; much collaboration with design teams is expected.

• Strong coding skills, preferably in Python, C++.

• Ability to formulate and analyze algorithms, and comment on their time complexity and memory consumption.

• Desire to bring data-driven decision-making and analytics to improve our products.

Ways to stand out from the crowd:

• Familiar with the power tools/flow development is a big plus

What you will be doing:

• Develop and optimize the control stack, including locomotion, manipulation, and whole-body control algorithms;

• Deploy and evaluate neural network models in physics simulation and on real humanoid hardware;

• Design and maintain teleoperation software for controlling humanoid robots with low latency and high precision;

• Implement tools and processes for regular robot maintenance, diagnostics, and troubleshooting to ensure system reliability;

• Monitor teleoperators at the lab and develop quality assurance workflows to ensure high-quality data collection;

• Collaborate with researchers on model training, data processing, and MLOps lifecycle.

What we need to see:

• Bachelor’s degree in Computer Science, Robotics, Engineering, or a related field;

• 3+ years of full-time industry experience in robotics hardware or software full-stack;

• Hands-on experience with deploying and debugging neural network models on robotic hardware;

• Ability to implement real-time control algorithms, teleoperation stack, and sensor fusion;

• Proficiency in languages such as Python, C++, and experience with robotics frames (ROS) and physics simulation (Gazebo, Mujoco, Isaac, etc.).

• Experience in maintaining and troubleshooting robotic systems, including mechanical, electrical, and software components.

• Physically work on-site on all business days.

Ways to stand out from the crowd:

• Master’s or PhD’s degree in Computer Science, Robotics, Engineering, or a related field;

• Experience at humanoid robotics companies on real hardware deployment;

• Experience in robot hardware design;

• Demonstrated Tech Lead experience, coordinating a team of robotics engineers and driving projects from conception to deployment.

What you will be doing:

• Collaborate closely with our AI/ML researchers to make their ML models more efficient leading to significant productivity improvements and cost savings

• Build tools, frameworks, and apply ML techniques to detect & analyze efficiency bottlenecks and deliver productivity improvements for our researchers

• Work with researchers working on a variety of innovative ML workloads across Robotics, Autonomous vehicles, LLM’s, Videos and more

• Collaborate across the engineering organizations to deliver efficiency in our usage of hardware, software, and infrastructure

• Proactively monitor fleet wide utilization patterns, analyze existing inefficiency patterns, or discover new patterns, and deliver scalable solutions to solve them

• Keep up to date with the most recent developments in AI/ML technologies, frameworks, and successful strategies, and advocate for their integration within the organization.

What we need to see:

• BS or similar background in Computer Science or related area (or equivalent experience)

• Minimum 8+ years of experience designing and operating large scale compute infrastructure

• Strong understanding of modern ML techniques and tools

• Experience investigating, and resolving, training & inference performance end to end

• Debugging and optimization experience with NSight Systems and NSight Compute

• Experience with debugging large-scale distributed training using NCCL

• Proficiency in programming & scripting languages such as Python, Go, Bash, as well as familiarity with cloud computing platforms (e.g., AWS, GCP, Azure) in addition to experience with parallel computing frameworks and paradigms.

• Dedication to ongoing learning and staying updated on new technologies and innovative methods in the AI/ML infrastructure sector.

• Excellent communication and collaboration skills, with the ability to work effectively with teams and individuals of different backgrounds

Ways to stand out from the crowd:

• Background with NVIDIA GPUs, CUDA Programming, NCCL and MLPerf benchmarking

• Experience with Machine Learning and Deep Learning concepts, algorithms and models

• Familiarity with InfiniBand with IBOP and RDMA

• Understanding of fast, distributed storage systems like Lustre and GPFS for AI/HPC workloads

• Familiarity with deep learning frameworks like PyTorch and TensorFlow

What you’ll be doing:

• Analyze state of the art DL networks (LLM etc.), identify and prototype performance opportunities to influence SW and Architecture team for NVIDIA's current and next gen inference products.

• Develop analytical models for the state of the art deep learning networks and algorithm to innovate processor and system architectures design for performance and efficiency.

• Specify hardware/software configurations and metrics to analyze performance, power, and accuracy in existing and future uni-processor and multiprocessor configurations.

• Collaborate across the company to guide the direction of next-gen deep learning HW/SW by working with architecture, software, and product teams.

What we need to see:

• BS or higher degree in a relevant technical field (CS, EE, CE, Math, etc.).

• Strong programming skills in Python, C, C++.

• Strong background in computer architecture.

• Experience with performance modeling, architecture simulation, profiling, and analysis.

• Prior experience with LLM or generative AI algorithms.

Ways to stand out from the crowd:

• GPU Computing and parallel programming models such as CUDA and OpenCL.

• Architecture of or workload analysis on other deep learning accelerators.

• Deep neural network training, inference and optimization in leading frameworks (e.g. Pytorch, TensorRT-LLM, vLLM, etc.).

• Open-sourceAIcompilers (OpenAI Triton, MLIR, TVM, XLA, etc.).

What you’ll be doing:

• Identify, run graphics, studio and WinAI benchmarks across servers, PCs, workstations and laptops.

• Compose competitive analysis reports for internal and external customers to position NVIDIA products appropriately using their evaluation.

• Develop and maintain automation scripts for games/studio/WinAI performance and system monitoring data collection on Windows and Linux to speed up providing business and engineering insights.

• Develop, implement and maintain tools to improve testing efficiency.

What we need to see:

• Pursuing BS in Computer Science or similar computer discipline.

• Good knowledge of Python or other scripting languages.

• Experienced and passionate about PC games or content creation.

• Linux and Windows knowledge.

• Good knowledge of PC systems and components.

• Capability to work with a lot of data.

• Good organizational, time management and task prioritization skills.

Ways to stand out from the crowd:

• Familiar with GenAI or LLM is a plus.

• Knowledge of OpenGL, Direct X and D3D.

• Knowledge of Data Visualization.

• Good knowledge of NVIDIA GeForce and RTX PRO series.