Internship - Embedded AI Application Engineering

Infineon Technologies; Singapore; On-site; SGD 16,000 - 22,000; Full time

Job summary

Infineon Technologies in Singapore offers an internship to build and deploy AI/ML solutions for embedded and edge devices. You will work on sensor data processing, model development, optimization, and deployment on microcontrollers, gaining hands-on experience across the end-to-end AI/ML lifecycle on resource-constrained hardware.

Responsibilities include data collection and preprocessing, training and optimizing models, and validating deployments on real devices, with learning outcomes focused

Qualifications

• Bachelor's in Electrical/Electronics engineering or related field.
• Basic knowledge of AI/ML concepts and data preprocessing techniques.
• Familiarity with Python and ML frameworks such as TensorFlow or PyTorch.
• Understanding of embedded systems or microcontrollers.
• Strong analytical and problem-solving skills.
• Interest in edge AI and embedded applications.

Responsibilities

• Data Management: Work with sensor data collection and preprocessing.
• Model Development: Build and train AI/ML models.
• Model Optimization: Optimize models for embedded deployment.
• Deployment & Testing: Test and deploy solutions on microcontrollers.

Skills

Python

TensorFlow/PyTorch

AI/ML foundations

Embedded systems

Data preprocessing

Analytical skills

Independent learning

Education

Bachelor's in Electrical/Electronics engineering or related field

Tools

TensorFlow

PyTorch

Job description

This internship focuses on building and deploying AI/ML solutions for embedded and edge devices. The role involves sensor data processing, model development, optimization, and deployment on microcontrollers.

Your Role

• Data Management: Work with sensor data collection and preprocessing
• Model Development: Build and train AI/ML models
• Model Optimization: Optimize models for embedded deployment
• Deployment & Testing: Test and deploy solutions on microcontrollers

Internship learning outcomes

• End-to-End AI/ML Experience: Gain hands‑on experience in the end‑to‑end AI/ML lifecycle, from data acquisition to model deployment on edge devices
• Model Efficiency: Develop skills in model quantization, compression, and optimization for resource‑constrained microcontrollers
• Research Application: Learn to implement and evaluate state‑of‑the‑art AI techniques based on current research literature
• Embedded AI Debugging: Acquire practical expertise in debugging, testing, and tuning embedded AI systems for real‑world applications

Your Profile

Qualifications And Skills To Help You Succeed

• Education: Bachelor's in Electrical/Electronics engineering or any related field
• AI/ML Foundations: Basic knowledge of AI/ML concepts and data preprocessing techniques
• Technical Proficiency: Familiarity with Python and machine learning frameworks such as TensorFlow or PyTorch
• Embedded Systems Knowledge: Understanding of embedded systems or microcontrollers
• Analytical Skills: Strong analytical and problem‑solving skills
• Industry Interest: Interest in edge AI, embedded applications, and emerging technologies
• Self‑Learning Ability: Ability to learn independently and work with technical documentation or research papers

Contact

Hillary Woo