We are looking for a hands-on Embedded Systems Engineer with AI/ML algorithm experience to develop next-generation Edge Control and AI solutions for Electric Vehicle applications. The role combines embedded firmware, real-time control, AI/ML algorithms, sensor processing and Edge AI deployment across battery, motor and power-electronics systems. Key Responsibilities • Develop Embedded C/C++ firmware for real-time EV control applications. • Develop and integrate control functions for BMS, motors, power electronics and sensors. • Interface ADC, PWM, GPIO, timers, SPI, I²C, UART and CAN/CAN-FD. • Develop battery functions including SoC/SoH estimation, cell monitoring, balancing, diagnostics and protection. • Develop BLDC/PMSM motor-control functions including FOC, SVPWM and current/voltage sensing. • Develop embedded control for DC-DC converters, OBC and EV energy-management systems. • Develop and deploy AI/ML algorithms for battery, motor and sensor applications. • Develop TinyML/Edge AI solutions using TI MSPM0G5187 and AM13Ex MCUs with NPU acceleration. • Prototype and validate Edge AI applications using NVIDIA Jetson, Raspberry Pi + AI HAT+ and Arduino VENTUNO Q. • Perform board bring-up, debugging, testing and hardware/software integration. • Optimize algorithms and embedded software for real-time performance, memory, latency and power consumption. Required Qualifications & Skills • Bachelor's/Master's degree in Embedded Systems, Electronics, Electrical/Electronics Engineering, Computer Engineering, or a related field. • 2–3 years of hands-on embedded software/firmware development. • Strong Embedded C/C++ programming skills. • Good understanding of microcontrollers, real-time systems, interrupts, timers, ADC and PWM. • Experience with CAN/CAN-FD, SPI, I²C and/or UART. • Fundamentals of AI/ML algorithms, signal processing or data-driven algorithms. • Ability to implement/deploy algorithms on embedded platforms. • Hands-on experience with JTAG/SWD, oscilloscope, logic analyzer and debugging tools. • Good understanding of hardware-software integration. Preferred Skills • BMS, motor control or power electronics. • FOC, SVPWM and PI/PID control. • TI MSPM0/MSPM0G, C2000, STM32, NXP or Infineon platforms. • FreeRTOS or other RTOS. • TinyML, Edge AI, NPU or embedded ML deployment. • MATLAB/Simulink. • Python and AI/ML frameworks. • NVIDIA Jetson or Raspberry Pi. • Git/GitHub. • Automotive communication and diagnostics. Development Focus Battery Management | Motor Control | Power Electronics | Sensors | AI/ML Algorithms | TinyML/NPU | Edge AI | Real-Time Control | EV Energy Management What You Will Build Develop reusable Edge Control technologies from evaluation-board prototypes to functional demonstrators for future EV platforms. Sensor → Embedded Control → AI/ML → Edge Inference → Decision → Real-Time Control Ideal candidate: An embedded engineer who can combine firmware development + control algorithms + AI/ML algorithms to solve real-world EV engineering problems. Interested in building the next generation of AI-enabled EV control systems? Apply or DM us.
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