[R&D]Embedded Software Engineer（2027 New Graduates）
Confirmed on the employer's own hiring board on Oct 15, 2026. First seen by Alion on Sep 24, 2026.
About Enactic
Building humanoids that learn to care, for facilities and homes worldwide.
Enactic is a deeptech startup building assistive humanoid robots that support and enrich daily life. As aging demographics accelerate and labor shortages grow, we deploy robots where help is needed most: in care facilities and homes.
Responsibilities
As our Embedded Software Engineer, you will be responsible for developing the core real-time software systems used in humanoid robots.
You will work at the intersection of software, hardware, firmware, AI, and manufacturing to build high-speed, highly reliable, and safe robot-control software.
The role involves optimizing everything from low-level sensor signal processing to actuator control, driving seamless integration between physical hardware and software.
Through this work, you will help elevate R&D-stage robots to a level suitable for mass production and global deployment.
Requirements
・Proficiency in embedded system development using C/C++
・Experience with low-level development for microcontrollers and real-time control
・Experience developing control software or firmware for robotic systems or mechatronic products
・Knowledge of electrical and electronic circuits and hardware debugging skills (e.g., signal analysis with an oscilloscope), with the ability to troubleshoot effectively at the interface between software and hardware.
Bonus Qualifications
・Knowledge of real-time computation such as RTOS kernels, task scheduling, and interrupt handling, and experience developing kernel modules or implementing device drivers in embedded Linux
・Experience implementing and troubleshooting communication protocols such as CAN, I2C, SPI, and EtherCAT, with practical knowledge of synchronized control, interrupt processing, and resource sharing in embedded systems
・Experience implementing algorithms based on control theory (e.g., PID control, state-space representation, model predictive control), and the ability to design and implement dynamic models and feedback control for robotic systems.