Research Intern in FPGA Deep-Learning Accelerator Design

Research Intern in FPGA Deep-Learning Accelerator Design
Location: bay area or remote
Term: 3-6 months
Job Description:
Come join Moffett.ai to build exciting revolutionary end-to-end machine learning solutions. We have openings for research intern to work on end-to-end FPGA-based machine learning accelerator projects for real-world applications.
This role offers a great opportunity to learn and become an expert in emerging deep learning algorithm, system and architecture. The successful candidate will work on state-of-the-art deep learning accelerator architecture and will contribute to an end-to-end FPGA solution for various applications. You will work with industry veterans and machine learning patent holders, and gain experience in full-stack hardware accelerator design flow including architecture and RTL, compiler, firmware and runtime.
You will also gain experiences in advanced pathfinding and forward-looking research, which may lead to novel inventions and/or papers published at top conferences.
Minimum Qualifications:
2+ years of experience in the following areas:
- Computer architecture
- Digital design. Expertise in RTL e.g., Verilog
- FPGA prototyping design, implementation, verification, debug, bring-up
- Software application development and profiling
Preferred Qualifications:
- Experience with Xilinx FPGA development
- Expertise in deep learning and hardware accelerator design
- Current Ph.D. students with 2+ years of research experience
Please email resume to join@moffett.ai