NVIDIA 2027 New College Graduate: GPU Architecture Engineering - China

Overview

• 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.
• Potential NCG opportunities in this field include: GPU Architecture Modeling and Performance Analysis 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.
• SoC Performance Simulation and Workload Analysis 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.
• GPU/System Functional Validation Platform Development 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.
• GPU Functional Verification and Test Generation 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.
• GPU and Memory-System Architecture Exploration Explore novel GPU composition, processing, storage, and memory-system capabilities; partner with architects to validate new features and improve performance, functionality, and test coverage.
• Performance Profiling, Debugging, and Optimization Profile system and application behavior, diagnose GPU/SoC performance bottlenecks, and develop tools and methodologies that improve analysis efficiency and overall application performance.
• Simulation, Emulation, and Silicon Bring-Up 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.
• What we need to see: 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.