Senior System Simulation Architect
NVIDIAJob Title
Senior System Simulation Architect
Role Summary
Develop and maintain full-system functional simulation and emulation infrastructure focused on CPU subsystems to evaluate performance for CPU/GPU heterogeneous workloads. Work closely with CPU architects, software engineers, and performance teams to bring up firmware, OS, drivers, benchmarks, and representative workloads in simulation and emulation.
Position sits on the CPU performance architecture team and supports next-generation CPU architecture development for high-performance computing and AI applications.
Experience Level
Senior — 6+ years of relevant experience.
Responsibilities
Key responsibilities include building and integrating simulation infrastructure and enabling software and workloads to run on those platforms.
- Design and develop full-system functional models able to run complex multithreaded heterogeneous (CPU/GPU) workloads, with emphasis on CPU subsystems.
- Integrate functional models from different frameworks with RTL simulators, emulators, hardware-in-the-loop, and performance models.
- Bring up system and application software in simulation and emulation, including firmware, Linux, drivers, benchmarks, and DL/HPC workloads.
- Port, extend, and develop system software (firmware, OS, drivers) to meet workload simulation requirements.
- Support architects and performance engineers in using functional and performance models and emulation to evaluate and tune CPU designs.
Requirements
Must-have technical skills and experience; nice-to-have items listed separately.
- Must-have: Strong programming ability in C, C++, and Python.
- Experience developing functional simulators and/or low-level software (OS, firmware, drivers); preferably both.
- Strong system- and application-level debugging skills.
- Experience with the ARM instruction set architecture.
- Effective communication and teamwork skills.
- Nice-to-have: Experience with hardware emulators and/or FPGAs.
- Background in CPU workload analysis (e.g., SimPoint).
- Experience with Linux kernel bring-up and debug.
- Familiarity with CUDA and GPU workflows.
- Experience developing and optimizing CPU/GPU applications in PyTorch, TensorFlow, or similar frameworks.
Education Requirements
Bachelor's or Master's degree in Electrical Engineering, Computer Engineering, Computer Science, or a related technical field, or equivalent practical experience.
About the Company
Company: NVIDIA
Headquarters: Santa Clara, California, USA
NVIDIA is a global leader in accelerated computing, renowned for its innovative solutions in AI and digital twins that transform diverse industries. The company specializes in networking technologies, providing end-to-end InfiniBand and Ethernet solutions for servers and storage that optimize performance and scalability. NVIDIA serves sectors such as high-performance computing, enterprise data centers, and cloud computing, constantly reinventing its products and services to stay ahead in the market.
