Santa Clara, CA, USA
1. In this role, you’ll architect, simulate, and design amazing machine learning accelerator architecture for Moffett AI solutions. You will interact with cross functional engineering teams to identify opportunities and requirements. Some of the job duties include:
2. Implement performance, functional and power model for AI accelerator architecture exploration and functional verification
3. Develop tests, test plans, and testing infrastructure to verify new algorithm and functionality and their performance
4. Develop customized high-performance computation library on AI chip
5. Assess new SW/HW innovations and drive the most relevant into the AI Chip Architecture definition
6. Research the industry trend and customer requirement of the machine learning algorithms and accelerators and drive partnerships for access to the most advanced technologies
1. Master/PhD degree in CS/EE/Math or equivalent
2. 2+ year industry or academic experience with GPU architecture or AI chip architecture
3. Knowledge/Experience in CPU/GPUs architecture with a focus on data-path, scheduler, memory system and network-on-chip interconnection design
4. Knowledge/Experience in OpenCL/CUDA/Metal or other such parallel programming APIs
5. Knowledge/Experience in GPU compiler design and machine learning compiler optimization
6. Experience/Knowledge in Machine Learning/Deep Learning and experience with frameworks like PyTorch, TensorFlow is a big plus
7. Experience with performance simulation and modeling in C++/python
8. Experiences on hardware and RTL implementation (Verilog/System Verilog) is a good plus
9. Passionate in new technology and innovation with strong communication skills