Software Architect Enterprise Ai 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:

As a valued member of the team, you will be involved in the technical design and implementation of numerous features working in an agile environment. In this role you can expect to:

• Create developer tools features for NVIDIA GPUs that enables developers to quickly iterate on optimizations to build fast graphics applications.

• Write fast, effective, maintainable, reliable and well documented code.

• Effectively estimate and prioritize tasks in order to build a realistic delivery schedule.

• Provide peer reviews to other engineers including feedback on performance, scalability and correctness.

• Drive technology discussions and provide valuable feedback about the architecture as a domain expert.

• Document requirements and designs, and review documents with stakeholders.

• Demonstrate growth in technical and non-technical abilities.

• Meet with the QA Department to develop a test plan for new features.

What we need to see:

• Pursuing BS or MS degree in one of the areas of Electrical Engineering, Computer Engineering, Computer Science.

• Excellent C++ programming skills and ability to articulate key aspects of Object-Oriented Programming.

• Proficient in at least one graphics programming API such as Direct3D, OpenGL and Vulkan.

• Able to work effectively with a team of engineers in a fast paced and dynamic environment.

• Excellent written and verbal communication skills.

• Able to estimate effectively to ensure delivery of software on time.

Ways to stand out from the crowd:

• Knowledge of 3D Graphics Algorithms and GPU Architectures.

• Strong grasp of heterogeneous computing, multithreading and a deep understanding of streaming multiprocessors, warp scheduling etc...

• Experience with GPU low-level performance tuning/optimization, including profiling and debugging.

• Solid understanding of User Experience (UX) design, GUI development and the Qt framework is a huge plus.

What you’ll be doing:

• Design and Implement API tests for CUDA driver and library.

• Automate CUDA tests, design test plan and enable them in automation testing infrastructure.

• Triage test results, isolate test failures and improve test coverage.

What we need to see:

• Can work 4 days a week for at least 1 year

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

• Familiar with programming and debugging skills with C/C++ and Python.

• Interested in test cases development, tests automation and failure analysis.

• Experience using AI development tools to improve quality and productivity across the end-to-end QA workflow.

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

Ways to stand out from the crowd:

• Strong English communication and collaboration skills.

• Familiar with parallel programming, ideally CUDA C/C++, is a plus.

• Background with Bullyseye, Gcov or other dev tool 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:

• 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.

Intelligent machines powered by AI computers that can learn, reason and interact with people are no longer science fiction. Today, a self-driving car can meander through a country road at night and find its way. An AI-powered robot can learn motor skills through trial and error. This is truly an extraordinary time — the era of AI has begun. Image recognition and speech recognition — GPU Deep Learning has provided the foundation for machines to learn, perceive, reason and solve problems. The GPU started out as the engine for simulating human creativity, conjuring up the amazing virtual worlds of video games and Hollywood films.

What you will be doing:

• Study and develop cutting-edge techniques in deep learning, graphs, machine learning, and data analytics, and perform in-depth analysis and optimization to ensure the best possible performance on current- and next-generation GPU architectures.

• Work directly with key customers to understand the current and future problems they are solving and provide the best AI solutions using GPUs.

• Collaborate closely with the architecture, research, libraries, tools, and system software teams at NVIDIA to influence the design of next-generation architectures, software platforms, and programming models.

• Some travel is required for conferences and for on-site visits with customers.

What we need to see:

• A degree from a leading university in an engineering or computer science related discipline (BS; MS or PhD preferred) or equivalent experience

• Strong knowledge of C/C++, software design, programming techniques, or AI algorithms

• Strong verbal and written communication skills in English and organization skills, with a logical approach to problem solving, time management, and task prioritization skills