Internship - Embedded AI Application Engineering

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 Key responsibilities in your new 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
• Preferred intake: Jan 27 - May/ June 27

Contact: Hillary Woo

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