About the job

【About the Role】

Join our pioneering team to redefine the future of local inference for AI models and ecosystems. We are building an FPGA-based general computation systems as a superior alternative to GPUs for Large Language Model (LLM) acceleration in Edge and Open Radio Access Network (O-RAN) environments. You will lead the hardware design, optimizing and accelerating high-performance AI inference on FPGA-based platforms.

【Key Responsibilities】

• FPGA Development: Architect, optimize, and develop hardware acceleration designs for local inference of LLMs on AMD FPGA platforms. Perform synthesis, place-and-route, timing closure, and power analysis. Debug FPGA-related issues using built-in logic analyzers with JTAG debuggers.
• IP Development and Integration: Develop/optimize key IPs such as MIGs/PCIe/DMA cores/parallel computing entities at RTL. Create testbenches and verification...