Ai Computing Architect Intern - jobs at Nvidia in China, Shanghai

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:

• 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

What you’ll be doing:

• Apply Machine Learning, Deep Learning techniques to overcome QA and Automation challenges for different NVIDIA Product lines

• Maintain and optimize new and existing automated tests with AI solution

• Design, implement and augment existing test frameworks with AI automation tools to reduce manual development efforts and make the current automation framework more productive and smart

• Work closely and collaboratively with other development and QA teams to gather automation requirements and review automation design

What we need to see:

• Pursuing Master or higher degree in computer science or electrical engineering with strong academics

• Good programming skills in python, proficient in applying OOP concepts and Data structures

• Good experience with using AI development tools for test plan creation, automation framework and test case development

• Have experience on using Cursor, MCP, Coderabbit for script generation/review

• Hands on experience in solving complex problems using AI technology or tools such as RAG, LLM/vLLM and AIGC

• Experience with large or complex applications and knowledge of code optimization and manipulation

• Demonstrates excellent communication skills, maintains a strong sense of initiative and motivation, and consistently upholds high standards for software quality

• Ability to work closely & collaboratively with other Development & QA teams especially across geographies

Ways to stand out from the crowd:

• Programming skills in C# is a plus

• Knowledge of Linux, Mac and Android is a plus

• Experience on Machine Learning Frameworks like Pytorch, Keras with TensorFlow, ONNX , and TensorRT is a plus

• Background of RL(Reinforce learning), or Meta-learning, or Life-long learning is a plus.

• Knowledge of SQL/NoSQL Database is plus

What you will be doing:

• Develop and optimize the control stack, including locomotion, manipulation, and whole-body control algorithms;

• Deploy and evaluate neural network models in physics simulation and on real humanoid hardware;

• Design and maintain teleoperation software for controlling humanoid robots with low latency and high precision;

• Implement tools and processes for regular robot maintenance, diagnostics, and troubleshooting to ensure system reliability;

• Monitor teleoperators at the lab and develop quality assurance workflows to ensure high-quality data collection;

• Collaborate with researchers on model training, data processing, and MLOps lifecycle.

What we need to see:

• Bachelor’s degree in Computer Science, Robotics, Engineering, or a related field;

• 3+ years of full-time industry experience in robotics hardware or software full-stack;

• Hands-on experience with deploying and debugging neural network models on robotic hardware;

• Ability to implement real-time control algorithms, teleoperation stack, and sensor fusion;

• Proficiency in languages such as Python, C++, and experience with robotics frames (ROS) and physics simulation (Gazebo, Mujoco, Isaac, etc.).

• Experience in maintaining and troubleshooting robotic systems, including mechanical, electrical, and software components.

• Physically work on-site on all business days.

Ways to stand out from the crowd:

• Master’s or PhD’s degree in Computer Science, Robotics, Engineering, or a related field;

• Experience at humanoid robotics companies on real hardware deployment;

• Experience in robot hardware design;

• Demonstrated Tech Lead experience, coordinating a team of robotics engineers and driving projects from conception to deployment.