applicants

Key Responsibilities

• Develop, train, test, and optimize machine learning models (vision, detection, classification, prediction, etc.).
• Integrate AI/ML models with hardware systems such as microcontrollers, sensors, cameras, and edge devices.
• Work closely with embedded and electronics teams to deploy AI models on edge platforms (Jetson, Raspberry Pi, ESP32, etc.).
• Implement real-time data processing pipelines for sensor or camera inputs.
• Support ongoing projects involving robotics, automation, and IoT/AI solutions.
• Troubleshoot and fine-tune AI performance on hardware for speed, power efficiency, and reliability.
• Document development processes, model behavior, and integration steps.
• Collaborate with software, mechanical, and hardware teams to deliver end-to-end product solutions.

Required Qualifications

• Bachelor’s degree in AI/ML, Computer Science, Electronics, Mechatronics, or related field.
• 1+ year of hands-on experience in machine learning or deep learning projects.
• Strong understanding of ML frameworks (TensorFlow, PyTorch, OpenCV, Scikit-Learn).
• Experience with hardware integration and working with edge devices or embedded platforms.
• Knowledge of Python programming and ML model deployment.
• Familiarity with sensors, camera modules, and microcontrollers.
• Ability to work with cross-functional engineering teams.
• Problem-solving mindset with strong analytical and debugging skills.

Additional (Preferred) Skills

• Experience with NVIDIA Jetson, Coral TPU, or similar edge AI platforms.
• Understanding of robotics applications (SLAM, object tracking, navigation, etc.).
• Basic knowledge of IoT protocols and cloud data pipelines.
• Experience with real-time applications or optimization for low-power devices.