NVIDIA 2027 New College Graduate: GPU Architecture Engineering - China

By submitting your resume, you’re expressing interest in one of our 2027 GPU Architecture Engineer – New College Grad roles. We’ll review resumes on an ongoing basis, and a recruiter may reach out if your experience fits one of our new college graduate opportunities. NVIDIA pioneered accelerated computing to tackle challenges no one else can solve. Our work in AI and digital twins is transforming the world's largest industries and profoundly impacting society — from gaming to robotics, self-driving cars to life-saving healthcare, climate change to virtual worlds where we can all connect and create.  

We offer an excellent opportunity to expand your career and get hands on experience with one of our industry leading GPU Architecture teams. We’re seeking strategic, ambitious, hard-working, and creative individuals who are passionate about helping us tackle challenges no one else can solve.  

Conduct quantitative studies of current and future GPU architectures; develop performance and functional models; analyze graphics and parallel-compute pipelines; identify bottlenecks and propose architectural improvements. 

Build and enhance performance simulators and modeling frameworks; capture, replay, and profile complex real-world application workloads; evaluate current and next-generation SoC performance across use cases. 

Develop pre-silicon programming and test environments for next-generation GPU and system features; work across architecture, hardware, and software teams throughout the chip development lifecycle. 

Create directed and constrained-random test plans with strong coverage; generate, run, and debug tests across functional simulators, unit- and full-chip RTL, emulators, and post-silicon platforms. 

Explore novel GPU composition, processing, storage, and memory-system capabilities; partner with architects to validate new features and improve performance, functionality, and test coverage. 

Profile system and application behavior, diagnose GPU/SoC performance bottlenecks, and develop tools and methodologies that improve analysis efficiency and overall application performance. 

Validate designs across multiple stages—from architectural models and RTL simulation to emulation and real silicon—and debug functional or performance issues before and after product release. 

• Expected to graduate in 2027 with a Bachelor's, Master's, or PhD degree in Electrical Engineering, Computer Engineering, or a related field 

• Computer Architecture, GPU Architecture, Microprocessor Design, or Memory Systems 

• C/C++, Python, Linux, and object-oriented software development 

• GPU programming and debugging, including CUDA 

• Performance/functional modeling, profiling, trace-driven or execution-driven simulation 

• Computer systems, compilers, assembly language, and system modeling tools such as SystemC 

• ASIC design, verification, RTL, random-test development, or post-silicon validation 

• Deep learning model development or AI workload optimization