Gpu Full Chip Random Verification Architect 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

• Develop comprehensive test plans and implement them using formal verification tools.

• Create assertions, assumptions, and cover properties to validate design behavior.

• Employ abstraction techniques to manage complexity and achieve verification goals.

• Analyze and debug failures in the RTL design.

• Collaborate with architecture, design, and verification teams to communicate coverage and ensure design quality.

What we need to see:

• BS/MS/PhD in CS, CE, EE, or Mathematics (or equivalent experience)with 3+ years relevant experience

• Strong problem-solving skills and the ability to thrive in a collaborative, distributed team environment.

• Proficiency in scripting languages like TCL, Python, or Perl.

Ways to stand out from the crowd:

• Hands-on experience with formal verification tools such as JasperGold or VC Formal.

• Experience with formal verification methodologies, SystemVerilog, and temporal logic.

What You Will Be Doing:

• Understand, modify, and improve an NVIDIA proprietary GPU compiler and assembler written in C++

• Design and develop new compiler passes and optimizations to produce best-in-class, robust, supportable compiler and tools

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

• Be part of a team that is at the center of deep-learning compiler technology spanning architecture design and support through functional languages

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 and maintainable solutions to challenging problems

• Good communication and documentation skills and self-motivated

Ways To Stand Out From The Crowd:

• Masters or PhD preferred, with some compiler code generation experience

• Experience in developing CUDA, DirectX, OpenGL/Vulkan applications

• Experience in performance analysis and compile time analysis tools

• Exposure to various ML techniques

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

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