Senior Solutions Architect Simulation jobs at Nvidia in China, Shanghai

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:

• Working with customers, partners, and IP vendors to understand SOC/IP solutions best suited for the target use cases and work with them to select and integrate appropriate IP/SOC solutions.

• Work with Architects, Chip Leads, and Customers on SOC/IP design, development, timing closure, power analysis, methodology alignment, and program execution to ensure pre-silicon and post-silicon targets are met.

• Integrating, evolving, and optimizing IP blocks across a range of products and use cases for

  NVIDIA
  SoCs in AI, driving, 6G, cloud, gaming, and other applications.

• Working with teams throughout the company (Architects, RTL, PD, Circuit, SI, Thermal, SW, Platform, Operations, Marketing, etc...) on implementing cross-team solutions to achieve project targets.

• Drive cross-team methodologies for external soft IP and PHY integration, Nvidia IP release to partner, RTL development and microarchitecture.

What we need to see:

• B.S. or M.S. in Computer Engineering or Electrical Engineering (or equivalent experience)

• 9+ years of relevant work experience in RTL development focused on CPU

  , GPU,
  and high-performance architectures.

• Proficiency in industry-standard RTL development and synthesis tools.

• Experience developing high-speed digital blocks.

• Experience debugging complex microarchitectural structures

• Strong interpersonal, communication, and teamwork skills.

• A drive to continuously learn and expand architectural breadth and depth.

• Ability to evaluate microarchitectural options for tradeoffs across design, verification, and PD.

• Experience interconnecting and analyzing complex microarchitectural structures and subsystems.

Ways to stand out from the crowd:

• Cross-cultural work and study experience

• Experience in ARM-based SOC definition and development

• Background in partner and customer engagement for usecase/chip solution.

• Experience in some of domains, SOC clock implementation, power structure insertion, DFT, synthesis, place and route and STA.

NVIDIA SOC System-ASIC team is hiring a verification engineer. In this role, you will work closely with Arch, design and verification engineers to thoroughly verify some top-level related control units (like: Fuse/Floorsweep, Strap, Reset, Sysctrl) and some silicon measurement related units from unit-level to fullchip-level. Those units are important IPs used in both NVIDIA GPU and Tegra products.

What you’ll be doing:

• Micro-architecture definition for System-level modules (Fuse, Strap, Floorsweep, In-silicon measurement, Reset, Sysctrl, etc...)

• Unit-level and System-level verification for System-level modules.

• Own some NVIDIA internal checks to guarantee the design quality.

What we need to see:

• BS / MS or equivalent experience in electrical / computer engineering and related.

• Above 5 years of ASIC design/verification experience.

• Familiar with verification methodology, tools and flow.

• Understand frontend ASIC design flow including RTL design, synthesis and timing analysis.

• Excellent analytical and problem-solving skills.

• Fluent English (both written and spoken) and excellent communication skills.

• Good team work spirit, easy to cooperate with team members.

Ways to stand out from the crowd:

• Broad knowledge with Video techniques, SOC architecture and Computer architecture is a big plus.

• Strong programming skills in C/C++, SystemVerilog, Perl and Python is appreciated as a plus.

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.