Summary:

　　Meta was built to help people connect and share, and over the last decade our tools have played a critical part in changing how people around the world communicate with one another. With over a billion people using the service and more than fifty offices around the globe, a career at Meta offers countless ways to make an impact in a fast growing organization.We are committed to advancing the field of artificial intelligence by making fundamental advances in technologies to help interact with and understand our world. Meta Reality Labs Research is looking for upcoming scientists and researchers with great interest in algorithm/hardware co-design and acceleration of AI machine learning applications, efficient sensing, and ML algorithms for AR/VR applications. Our team specializes in developing state-of-the-art hardware optimized algorithms for machine perception. With the vision of metaverse, our team is focusing on cutting edge systems that can facilitate AI assistants. This internship will focus on aspects of foundational AI technologies around multimodal understanding (audio, visual, spatial, etc), multitasking, privacy, or others that support AI assistant functionalities.Our internships are twelve (12) to sixteen (16), or twenty-four (24) weeks long and we have various start dates throughout the year.

　　Required Skills:

　　Research Scientist Intern, Edge Compute Architectures (PhD) Responsibilities:

　　Support architecture studies, performance analysis, and design studies

　　Participate in research activities focused on edge compute architecture

　　Minimum Qualifications:

　　Minimum Qualifications:

　　Currently has, or is in the process of obtaining a PhD in the fields of Electrical Engineering, Computer Science, or related field

　　2+ years of experience programming with Python

　　2+ years research experience in one or more of the following: Machine learning accelerator / inference engine for deep neural networks (DNN), Algorithms to perform low precision arithmetic for deep learning, Quantization and sparsity techniques for efficient inference, Computer architecture for mobile and/or embedded systems, Deployment of computer vision methods on embedded systems or Hardware design with Magma, Chisel, Google XLS, or any high level synthesis (HLS) languages

　　Preferred Qualifications:

　　Preferred Qualifications:

　　Experience developing or optimizing CV and ML algorithms for vision tasks

　　Experience with Tensorflow, Tensorflow Lite, and Pytorch software stack

　　Experience in system modeling for all aspects of a digital system

　　Experience with synchronous and asynchronous communication protocols (e.g. I3C, CSI-2, SPI, UCIe, PCIe)

　　Proven track record of achieving significant results as demonstrated by grants, or fellowships, as well as first-authored publications in major conferences and journals such as ISCA, MICRO, HPCA, ISSCC, TinyML, IEDM, VLSI Symposium, ASPLOS, JSSC, TCAS

　　Public Compensation:

　　$7,313/month to $11,333/month + benefits

　　Industry: Internet

　　Equal Opportunity:

　　Meta is proud to be an Equal Employment Opportunity and Affirmative Action employer. We do not discriminate based upon race, religion, color, national origin, sex (including pregnancy, childbirth, or related medical conditions), sexual orientation, gender, gender identity, gender expression, transgender status, sexual stereotypes, age, status as a protected veteran, status as an individual with a disability, or other applicable legally protected characteristics. We also consider qualified applicants with criminal histories, consistent with applicable federal, state and local law. Meta participates in the E-Verify program in certain locations, as required by law. Please note that Meta may leverage artificial intelligence and machine learning technologies in connection with applications for employment.

　　Meta is committed to providing reasonable accommodations for candidates with disabilities in our recruiting process. If you need any assistance or accommodations due to a disability, please let us know at [email protected].