Role overview
Renesas is seeking a Sr. Staff Embedded AI Engineer to develop advanced TinyML and embedded AI solutions targeting Renesas microcontroller and MPU platforms (RA, RL78, RX, RZ). This is a highly technical, hands-on role focused on building cloud-based model translation infrastructure and optimizing network inference for resource-constrained embedded systems. You will contribute to a small team developing a service that converts trained machine learning models into efficient C/C++ implementations for deployment on microcontrollers. The ideal candidate combines strong embedded software expertise with solid machine learning fundamentals and is comfortable working across the stack — from neural network internals to low-level performance optimization. You should be someone who contributes new ideas, challenges assumptions, and helps improve both tooling and embedded implementation quality
What we're looking for
- Experience developing inference runtimes, model translation tools, or code generation systems.
- Experience with CMSIS-NN or other embedded ML acceleration libraries.
- Experience optimizing quantized neural networks for embedded systems using SIMD/DSP acceleration.
- Familiarity with Renesas MCU/MPU platforms (RA, RL78, RX, RZ).
- Experience with real-time systems (RTOS or bare-metal).
- Hardware debugging experience.
20026082_2026-03-24