Research Scientist Intern, Multimodal Contextual AI (PhD)

Descripción del puesto:

At Reality Labs, our team brings novel experiences to life on Meta's AR devices. We are seeking upcoming scientists and researchers with great interest in real-time embedded software development and hardware acceleration to enable on-device contextual AI within the performance, power and form-factor constraints of AR glasses. Within the vast domain of contextual AI, we are currently focusing on three key areas: computer vision, audio interaction, and large language models. As a Research Scientist intern, you will help us advance the state-of-the-art in one or more of these areas. Our internships are twelve (12) to twenty-four (24) weeks long and we have various start dates throughout the year.
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. AOSP Collaborate with other researchers and engineers across various disciplines

Requerimientos del candidato/a:

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 the country of employment at the time of hire, and maintain on-going work authorization during employment Experience in HW+SW system prototyping using embedded device prototypes and FPGAs Experience in operating systems, drivers, and embedded firmware development Experience working in a machine learning framework, e.g. PyTorch Experience 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) Intent to return to degree-program after the completion of the internship/co-op Proven track record of achieving significant results as demonstrated by grants, fellowships, patents, as well as first-authored publications at leading workshops or conferences such as CVPR, ECCV/ICCV, SIGGRAPH, or similar