The intern will support the end-to-end workflow of building edge AI demonstrations on microcontrollers. Responsibilities include collecting and organizing sensor data, applying signal processing techniques, and developing machine learning models. The role involves deploying and validating these models on hardware to optimize performance metrics such as latency and accuracy. Additionally, the intern will document workflows and collaborate with the team to iterate on project results. This position provides hands-on experience with embedded systems and data processing in a professional setting.

Candidates must be enrolled full-time as a rising junior or senior undergraduate or a graduate student in Computer Engineering, Electrical Engineering, Computer Science, or a related field. Required technical proficiencies include programming in C, C++, and Python, as well as familiarity with embedded toolchains, Git, and signal processing concepts. Applicants should possess a basic understanding of machine learning algorithms and embedded hardware peripherals. A valid driving license is required for data collection tasks, and candidates must not have graduated before September 2026.