Meta Reality Labs (RL) is the world leader in the design of virtual and augmented reality systems. The RL Silicon Research Team is looking for exceptional interns to help us create the next-generation experiences in virtual and augmented reality. Our Silicon research and development focuses on exploring new circuit design techniques, architectures and technologies for future AR products. We are looking for students interested in architecting custom or semi-custom hardware to implement speech and voice detection models that maximize performance under fixed power and resource constraints. The ideal candidate will have a full stack understanding of machine learning systems from architecture down to hardware implementation and technology. Our internships are twelve (12) to twenty-four (24) weeks long and we have various start dates throughout the year.Must obtain work authorization in the country of employment at the time of hire and maintain ongoing work authorization during employment. Currently has, or is in the process of obtaining, a PhD degree in Electrical or Computer Engineering, Computer Science or related field. Experience in the architecture and design of digital SoC or analog/mixed-signal processing circuits using low-power techniques and industry-standard EDA tools. 1+ years experience in developing solutions using machine learning and/or deep learning frameworks. Intent to return to degree-program after the completion of the internship/co-op. Signal processing experience with voice and speech recognition applications. Familiarity with the microelectronic technology of MEMS microphone sensors. 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 ISSCC, VLSI Symposium, ESSCIRC, tinyML Symposium, ICASSP or similar. Hands-on relevant experience via internships, employment, coding competitions, chip tape outs. Experience working and communicating cross functionally in a team environment