Artificial Intelligence (AI) Intern EV Powertrain Systems

Job highlights

• Fresher or Pursuing Computer Science / Electronics / Robotics Engineering or related technical field with a heavy focus on Machine Learning
• Basic understanding of EV powertrain architecture,BMS logic,and MCU behaviors is highly preferred
• Hands-on experience with TinyML frameworks (TensorFlow Lite for Microcontrollers,Edge Impulse,etc.)

Integrate advanced Machine Learning algorithms and edge AI intelligence into core EV electronics like the BMS and MCU.

This is a hybrid position.

Work at the intersection of AI and embedded software to deploy intelligent predictive models directly onto our electric motorcycles electronic control units.

• Develop and deploy TinyML / edge ML models tailored for resource-constrained microcontrollers (MCU)

• Implement AI algorithms within the Battery Management System (BMS) for real-time State of Charge (SoC), State of Health (SoH) tracking, and predictive thermal management

• Optimize motor control unit (MCU) efficiency and torque profiles using real-time predictive modeling

• Collaborate with the embedded electronics team to map sensor data pipelines to AI inputs

• Simulate, test, and validate model behavior against physical motorcycle runtime constraints

• Fresher or Pursuing Computer Science / Electronics / Robotics Engineering or related technical field with a heavy focus on Machine Learning. This is an internship position, do not apply if you are already employed.

• Hands-on experience with TinyML frameworks (TensorFlow Lite for Microcontrollers, Edge Impulse, etc.)

• Strong mathematical and programming foundations in Python and embedded C/C++

• Familiarity with processing time-series data from sensors (current, voltage, temperature, speed)

• Basic understanding of EV powertrain architecture, BMS logic, and MCU behaviors is highly preferred

Disclaimer: This job posting has been aggregated from external source. Role details, content, and availability are subject to change. Applicants are advised to confirm the latest information directly on the company website before applying.