NVIDIA 2027 New College Graduate: Deep Learning and High-Performance Computing Engineering - China

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. Today, we’re tapping into the unlimited potential of AI to define the next era of computing. An era in which our GPU acts as the brains of computers, robots, and self-driving cars that can understand the world. Doing what’s never been done before takes vision, innovation, and the world’s best talent. As an NVIDIAN, you’ll be immersed in a diverse, supportive environment where everyone is inspired to do their best work. Come join the team and see how you can make a lasting impact on the world. We are looking for an outstanding Compiler Engineer to help build the next generation of intelligent compiler technologies for NVIDIA's accelerated computing stack. Our team works at the intersection of compilers, agentic systems, numerical correctness, and verification to create systems that can reason about, generate, optimize, and validate code transformations across software and hardware boundaries. This is an excellent opportunity for new graduates who are excited about coding agents, AI-assisted software engineering, developer tools, and GPU computing. In this role, you will work with experienced engineers and researchers to build agentic systems and compiler-aware tooling that improve developer productivity, code quality, and system performance across NVIDIA's software and hardware stack. What you'll be doing: Build and improve coding-agent systems for tasks such as code generation, transformation, debugging, optimization, validation, and developer assistance. Develop agent workflows involving tool use, planning, memory, execution, and feedback loops for software engineering and compiler-related tasks. Help create training, evaluation, and verification environments to improve agent quality, correctness, r

NVIDIA Research is seeking extraordinary networking innovators to join our NVResearch team. As a research intern on this team, you will contribute to the development of future high-performance networking and computing systems. We are seeking a balanced background of research excellence in building systems and a deep understanding and broad perspective across the fields of computer architecture and communication systems for distributed computation. NVIDIA has pioneered programmable GPUs and the CUDA language, and this visionary Research team will take those technologies to the next level with its creative ideas and new inventions. This position offers you the opportunity to have a real impact while working with some of the most creative and forward-thinking people in the world who are here at this dynamic, technology-focused company. What you'll be doing: Develop algorithms and design hardware and software, extending the state of the art in computing, networking, and other technology areas surrounding NVIDIA's business. Invent new techniques, technologies, methodologies, processes, and devices, to enable new products or types of products. Deliverable results include prototypes, patents, and publications. Contribute to research that informs NVIDIA's technology direction 5-10 years out. Work focuses on long-horizon problems rather than products currently shipping or in development, except as to how they can be extended and improved. Projects can include but are not limited to: optimizing communication stacks for AI training and inference, designing network protocols and congestion control, co-designing AI systems across software and hardware, developing circuits and microarchitecture for network controllers and switches, and architecting networks built on optical switching and silicon photonics. What we need to see: Pursuing a

NVIDIA is at the forefront of the AI and robotics revolution, and NVIDIA’s robotics teams are on a mission to build the essential technology that can enable any company to become a robotics company. The Seattle Robotics Lab is uniquely positioned at the intersection of open academic research and real-world industry impact, pursuing fundamental and applied robotics research across the full robotics stack, including perception, planning, control, reinforcement learning, imitation learning, simulation, and robotics foundation models. This research aims to transform research paradigms, transfer into NVIDIA’s robotics and simulation products, and create new robotics markets for the world. The Seattle Robotics Lab has published over 500 research papers, including many influential works that have been presented at top robotics, AI, and computer vision conferences. These works include BayesSim , cuRobo , DeXtreme , DiSECT , Factory , GraspNet , IndustReal , ITPS , LAPA , <a href="h

We are now looking for a Deep Learning Software Test Development Engineer Intern! The position is in NVIDIA Deep Learning Software Quality Assurance team that defines, develops and performs tests to validate robustness and measure the performance of NVIDIA‘s Deep Learning software and GPU Infrastructure for autonomous driving, healthcare, speech recognition, natural language processing, and a wide variety of other AI scenarios. This team collaborates with multiple AI product teams to develop new products; derive and improve complex test plans; and improve our workflow processes for a diverse range of GPU computing platforms. You should grow with being in the critical path supporting developers working for billion-dollar business lines as well as intimately understanding the values of responsiveness, thoroughness and teamwork. You should constantly foster and implement efficiency improvements across your domain. Join the team which is building software which will be used by the entire world! What you’ll be doing: Be responsible for functionality, compatibility, and performance tests in NVIDIA AI SW stack release. Develop, maintain, and improve test automation infrastructure with using AI tools. Use AI to improve quality and productivity across QA End-to-End workflow. Work with development teams to triage issues, root cause analysis, verify fixes, define new tests, improve test plans. What we need to see: Pursuing MS or higher degree in CS/EE/CE or a related field. Proven success in leveraging AI tools to significantly improve efficiency, streamline workflows or enhance process automation. Good python, C&#43;&#43; programming skillset, Linux knowledge is required. Experience in software development with popular AI model

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. Today, we’re tapping into the unlimited potential of AI to define the next era of computing. An era in which our GPU acts as the brains of computers, robots, and self-driving cars that can understand the world. Doing what’s never been done before takes vision, innovation, and the world’s best talent. As an NVIDIAN, you’ll be immersed in a diverse, supportive environment where everyone is inspired to do their best work. Come join the team and see how you can make a lasting impact on the world. With the continuous improvement of chip technology, design scale and performance/power ratio, the physical design of digital chips is facing outstanding challenges in high frequency, low power consumption and multiple applications. High efficiency, high quality of the implementation of the construction chip is the guarantee of the company's competitiveness. As an ASIC-PD intern at NVIDIA, you'll learn and work on the tasks from RTL frozen to tape out, include synthesis, formal verification, constraints definition, timing closure/sign off, study on the timing impact of process and related methodology work. What you'll be doing: Chip integration and netlist generation, cross-team collaboration to implement chip partitioning and floorplan Synthesis, RTL/netlist quality check, formal verification, function eco creation Constraints creation and validation, timing budget, work with ASIC team to analyze/resolve function timing issues, achieve all special timing closure, such as io, test, clock, async etc. Work in conjunction with PR engineers for chip implementation to achieve full chip timing closue Develop and improve entire timing closure flow from frontend (pre-layou

NVIDIA is the world leader in GPU Computing. We are passionate about markets including gaming, automotive, professional vision, HPC, datacenters and networking in addition to our traditional OEM business. NVIDIA is also well positioned as the ‘AI Computing Company’, and NVIDIA GPUs are the brains powering modern Deep Learning software frameworks, accelerated analytics, modern data centers, and driving autonomous vehicles. We have some of the most experienced and dedicated people in the world working for us. If you are dedicated, forward-thinking, and if working with hard-working technical people across countries sounds exciting, this job is for you. We are now looking for a Software QA Test Development Engineer, you will collaborate with multi-functional groups. SWQA test developer engineer at NVIDIA is responsible for test planning, execution, and reporting, you will also write scripts to automate testing, design and develop tools for QA team, or develop integration tests for validation, so QA engineer can improve productivity or optimize test plan. As a SWQA test developer, you must identify weak spots and constantly design better and creative test plans to break software and identify potential issues. You will have a huge impact on the quality of NVIDIA's products. What You’ll Be Doing Analyze requirements and design test matrices covering functionality, performance, and edge cases. Develop test plans and cases; build and maintain automated test suites (API / UI / CLI / E2E) in Python. Leverage AI-powered tools and agentic workflows to accelerate test generation, triage, and root cause analysis. Manage the full bug lifecycle — filing, reproduction, and driving multi-functional collaboration to resolution. Reproduce and verify customer-reported issues to ensure quality before release.