Preferred Background •Major in CS, Data Science, AI/ML, or Engineering •Familiarity with Python and common ML libraries •Interest in applied AI, ML systems, or AI-enabled applications
Internship Description
This internship provides hands-on learning exposure to embedded AI and edge intelligence, focusing on deploying lightweight AI models on resource-constrained hardware platforms. Participants will work on guided embedded AI projects, learning how AI models are adapted for real hardware environments.
Activities & Exposure
• Practice deploying AI/ML models on embedded devices
• Learn about model optimization, inference, and performance trade-offs
• Explore firmware and AI integration workflows
• Participate in testing and benchmarking of embedded AI systems
Outcomes
• Edge AI system design concepts
• Trade-offs between accuracy, latency, and power
• Communicating embedded AI design decisions
Requirements
CS, EE, CE, or related engineering majors
Familiarity with Python or C/C++
Interest in AI systems, edge computing, or embedded development