Research Intern, Embedded AI on Wearables (PhD)
meta platformsRedmond (WA)
Research Intern, Embedded AI on Wearables (PhD)
Posted 2 days ago
meta platformsRedmond (WA)
Computer and Information Research ScientistsResearch and Development in the Physical, Engineering, and Life Sciences
SENIORITY
Intern
About the role
Research Intern, Embedded AI on Wearables (PhD) Our team, within Reality Labs at Meta, brings novel experiences to life on Meta's AR and AI devices. We were closely involved in the development of multimodal Meta AI on Orion, and we are currently working on the next gen AR glasses. We are looking for upcoming scientists and researchers with great interest in real-time embedded software development and hardware acceleration to enable on-device AI within the performance, power and form-factor constraints of AR glasses. Within the vast domain of on-device AI, we are currently focussing on three key areas: computer vision, audio interaction, and large language models. As a Research Scientist intern, you will help us advance the SOTA in one or more of these areas. Build and characterize experimental HW+SW systems on AR devices and device prototypes Develop embedded firmware and software in RTOS and mobile operating systems, e.g. AOSPCollaborate with other researchers and engineers across various disciplines Currently has, or is in the process of obtaining a PhD in Computer Science, Electrical Engineering, or a related field Programming and simulation experience with languages such as C/C++ and Python Experience with computer architecture and HW/SW co-design and co-optimization Must obtain work authorization in country of employment at the time of hire, and maintain ongoing work authorization during employment Intent to return to full-time degree program after completion of the internship Experience in HW+SW system prototyping using embedded device prototypes and FPGAsExperience in operating systems, drivers, and embedded firmware development Experience working in a machine learning framework, e.g. PyTorchExperience working and communicating cross functionally in a team environment Demonstrated embedded software experience via an internship, work experience, coding competitions, or widely used contributions in open source repositories (e.g. GitHub)
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