Praktikum in der Technologieentwicklung – KI-basierte Sensorauswertung
Core
Develop and evaluate machine learning and deep learning solutions for sensor data classification and processing on microcontrollers for automotive applications.
Role type
Intern, embedded machine learning engineer
Builds
Reference and demonstration applications for ESP-Sensair-Shuttle hardware
Domain
Automotive technology, embedded systems, machine learning
Deliverable
production ML models
Required skills
Python, microcontroller programming, machine learning, deep learning
Preferred skills
TensorFlow Lite (Micro), Edge Impulse, ESP-DL, Random Forest
Technologies
ESP32, TensorFlow Lite (Micro), Edge Impulse, ESP-DL, Random Forest, Python
Responsibilities
Create classification concepts for sensor data recording and classification; Implement and evaluate classical machine learning approaches on microcontrollers; Develop and port deep learning approaches for ESP32; Evaluate hardware possibilities and create test projects; Develop reference and demonstration applications.
Seniority
Intern
