Senior Manager Hardware Engineering 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

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.

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

What you'll be doing:

• Work on NVIDIA's next generation of Video Decoder and Encoder hardware architecture.

• Research and study new video compression technology, specifications, papers etc.

• Develop c-model for algorithm study, hardware simulation and verification.

• Define the testplan, write architecture document, verify c-model and improve model coverage.

What we need to see:

• Master degree or above in Computer Science, Electronic Engineering.

• Minimum of 3 years' experience in the field of video technology ranging from codec, implementation, pre/post-processing, rate control and etc.

• Good programming skill and C/C++ coding abilities.

• Fluent English (both written and spoken) and good communication skill.

Ways to stand out from the crowd:

• Project experiences in video encoder, decoder or computer vision.

• Experience with video codec such as H264,HEVC, VP9, AV1or VVC.

• Experience with DL video/image processing.

• Creative, strong analysis, design and debug skill.

What you’ll be doing:

• Develop algorithms to exercise various parts of the GPU pipeline to verify our performance metrics.

• Deeply dive into NVIDIA GPU architecture and software stack, develop new feature for NVIDIA GPU performance profiling tools.

• Write unit and integration tests to verify the functionality, performance, stability, resource usage of our products.

What we need to see:

• Pursuing a Master's degree major in CS/SE.

• Proficiency in C/C++, object oriented programming.

• Proficiency in written and spoken English.

Ways to stand out from the crowd:

• OpenGL, GLES, Direct3D, Vulkan, CUDA, OpenCL, console graphics APIs.

• Experience of driver development.

• Background with software development for embedded systems.