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