Jobs at Nvidia in 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

What you’ll be doing:

• Work with architects and performance architects to develop an energy-efficient GPU.

• Develop methodologies and workflows to select and run a wide variety of workloads to train models using ML and/or statistical techniques.

• Develop methodologies to improve the accuracy of energy models under various constraints, such as, process, timing, floorplan and layout.

• Correlate the predicted energy from models created at different stages of the design cycle, with the goal of bridging early estimates to silicon.

• Develop tools to debug energy inefficiencies observed in various workloads run on silicon, RTL and architectural simulators. Work with architects to fix the identified energy inefficiencies.

• Work with performance, verification and emulation methodology and infrastructure development teams to integrate energy models into their platforms.

• Prototype new architectural features, create an energy model, and analyze the system impact.

What we need to see:

• MS degree with 1 year experience in related fields or equivalent experience

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

• Background in machine learning, AI, and/or statistical modeling.

• Interest in computer architecture and energy-efficient GPU designs.

• Familiarity with Verilog and ASIC design principles is a plus.

• Ability to formulate and analyze algorithms, and comment on their runtime and memory complexities.

• Desire to bring quantitative decision-making and analytics to improve the energy efficiency of our products.

• Good verbal/written English and interpersonal skills.

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

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 great technology—and amazing people.

• Design and implement the DSL and the core compiler of tile-aware GPU programming model for emerging GPU architectures

• Continuously innovate and iterate on the core architecture of the compiler to consistently optimize performance

• Investigation of next-generation GPU architectures and provide solutions in the DSL and compiler stack

• Performance analysis on emerging AI/LLM workloads and integrate with AI/ML frameworks

• Masters or PhD or equivalent experience in relevant discipline (CE, CS&E, CS, AI)

• 4 + years of relevant work experience

• Excellent C/C++ programming and software engineering skills, ACM background is a plus

• Good fundamental knowledges on computer architecture

• Strong ability in abstracting problems and the methodology in resolving problems

• Strong compiler backgrounds including MLIR/TVM/Triton/LLVM is desired

• Good knowledge of GPU architecture and fast kernel programming skills is a plus

• Knowledge of LLM algorithms or a certain HPC domain is a plus

• Knowledge of multi-GPU distributed communication is a plus

• Excellent oral communication in English is a plus

What you will be doing:

• Design and implementfunctional/performancetests for CUDA products, like driver and library.

• Automate CUDA tests, design test plans and integrate into automation testinginfrastructure.

• Triage test results, root cause test failures or performance drops, and drive through bugs to fix.

• Develop scripts/tools and optimize workflow to improve efficiency and productivity.

What we need to see:

• MS or PhD degree from a leading university in computer science or a related field.

• At least 3 years of relevant professional experience.

• Excellent QA sense, knowledge, and experience in software testing.

• Rich experience in test case development, tests automation and failure analysis.

• Proficient programming and debugging skills in C/C++ and Python.

• Comprehensive knowledge of Linux and Windows operating systems.

• Experience in using AI development tools for test plans creation, test cases development and test cases automation.

Ways to stand out from the crowd:

• Excellent English communication and collaboration skills.

• Strong understanding of CUDA, HPC, Gcov, VectorCAST, Coverity.

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

for an exciting and fun role in our, which covers the areas over runtime, compiler optimization, code generation, CPU pipeline analysis and etc.

What you'll be doing:

• Work on feature enablement and optimization of open source Java virtual machine projects.

• Partner with both internal and communities to develop, valid and upstream patches.

• Work with global compiler, hardware and application teams to oversee improvements and problem resolutions.

• Drive and push architecture neutral and NV friendly solutions in the communities.

• Be flexible, with a variety of software development skills and extend the breadth and depth of knowledge.

What we need to see:

• Pursuing B.S. or higher degree in Computer Science/Engineering

• Excellent hands-on C++ programming skills

• Strong background in software engineering principles with a focus on crafting robust andmaintainable solutions to challenging problems

• Good communication and documentation skills and self-motivated

Ways to stand out from the crowd:

• Masters or PhD preferred, with compiler or language virtual machine experiences

• Background with Java and understand the key language features

• Familiar with Linux and shell programming

• Knowledge on computer architecture, ISA, assembly, and Arm64 is preferred

• Exposure to various ML techniques