Key technologies and capabilities for this role
Common questions about this position
MSEE/MSCE (or equivalent experience) and 4+ years proven experience or PhD with specialization in Low Power Architectures or energy efficient design techniques is essential.
Design experience with industry tools such as SystemVerilog RTL, UVM, Verdi, UPF, VCS NLP, Python, C++ are essential, along with cross-discipline experience in HW/SW/System level interactions.
This information is not specified in the job description.
This information is not specified in the job description.
Background with HW/SW interactions, Power what ifs and tradeoffs, Clock tree power reduction and CG strategies, RAM power optimization, and experience with directed and random functional testing including writing test plans stand out.
Designs GPUs and AI computing solutions
NVIDIA designs and manufactures graphics processing units (GPUs) and system on a chip units (SoCs) for various markets, including gaming, professional visualization, data centers, and automotive. Their products include GPUs tailored for gaming and professional use, as well as platforms for artificial intelligence (AI) and high-performance computing (HPC) that cater to developers, data scientists, and IT administrators. NVIDIA generates revenue through the sale of hardware, software solutions, and cloud-based services, such as NVIDIA CloudXR and NGC, which enhance experiences in AI, machine learning, and computer vision. What sets NVIDIA apart from competitors is its strong focus on research and development, allowing it to maintain a leadership position in a competitive market. The company's goal is to drive innovation and provide advanced solutions that meet the needs of a diverse clientele, including gamers, researchers, and enterprises.