Arch Intern, DLA
at Nvidia
Posted 5 hours ago
No clicks
- Compensation
- Not specified
- City
- Shanghai
- Country
- China
Currency: Not specified
Join NVIDIA's NVDLA HW team to design architecture for deep learning accelerator IP and hardware/software integration. The Arch Intern will research, design, and develop architecture solutions for accelerating processors, focusing on deep-learning architectures, algorithms, and software development. The role involves developing function, performance, and power models for NVDLA and collaborating with cross-functional teams to deliver high-quality DL processors. This internship offers exposure to cutting-edge compute vision, processor architecture, and hardware-software prototyping in applications like Gaming, Robotics, and Autonomous Vehicles.
NVIDIA is building the world’s most groundbreaking and state of the art computing platforms for the world to use. NVIDIA NVDLA HW team delivers high quality deep learning accelerator IP to NVIDIA produce lines. Our team’s work includes Deep Learning algorithm, HW architecture/design/verification and SW prototyping. We are seeking a talented Deep Learning Architecture Engineer to design architecture for innovative deep learning projects and groundbreaking applications such as Gaming, Robotics, and Autonomous Vehicles. You will work with a very brilliant, creative, and helpful team, for a very complex problem that will help to make the world better.
What you’ll be doing:
- Research, design, and develop architecture solutions of NVIDIA’s accelerating processor
- Work on Deep-Learning architecture, algorithms, and software development
- Develop function/performance/power models for NVDLA
- Co-work with other teams to deliver high quality Deep-Learning processors
What we need to see:
- MS degree from EE/CS or related majors from a prestigious university.
- Experience in C/C++/Python/SystemC
- Proficient in English reading and writing.
- Self-motivated, good teammate.
Ways to stand out from the crowd:
- Ability to work independently as well as in a multi-disciplinary group environment
- Mastery in Compute Vision, Processor architecture, Pattern recognition/machine learning is a plus
- Hardware design or Deep Learning background is a plus.

