Research Scientist Intern, Edge Compute Architectures (PhD)

Meta's mission is to give people the power to build community and bring the world closer together. Through our family of apps and services, we're building a different kind of company that connects billions of people around the world, gives them ways to share what matters most to them, and helps bring people closer together. Whether we're creating new products or helping a small business expand its reach, people at Meta are builders at heart. Our global teams are constantly iterating, solving problems, and working together to empower people around the world to build community and connect in meaningful ways. Together, we can help people build stronger communities - we're just getting started.Meta Reality Labs Research is looking for emerging scientists and researchers with interest in full software-hardware co-design of always-on algorithms being deployed on form-factor constrained AR/VR devices. The main objective of this research is to explore methods to push the boundaries of what is possible on our constrained platforms. Our internships are sixteen (16) to twenty-four (24) weeks long and we have various start dates throughout the year.

• Support architecture studies, performance analysis, and design studies
• Participate in research activities focused on edge compute architecture

• Currently has or is in the process of obtaining a PhD in the fields of Electrical Engineering, Computer Engineering, Computer Science, or related field
• Must obtain work authorization in the country of employment at the time of hire and maintain ongoing work authorization during employment
• 2+ years of research experience in one or more of the following: machine learning accelerators or inference engines for deep neural networks (DNN), computer architecture for mobile or embedded systems (ARM/RISC-V ISA), deployment of computer vision algorithms on embedded systems
• Experience with deep learning frameworks (Pythorch, Tensorflow, etc.)
• Proficient with Python/C/C++

• Experience developing or optimizing CV and ML algorithms for vision tasks
• Experience in system modeling for all aspects of a digital system
• Proficiency in hardware description languages, including SystemVerilog (preferred), Verilog, VHDL, and Chisel, with experience in designing, simulating, and implementing digital systems
• Experience with FPGA design, development, and implementation using industry-standard tools (e.g., Xilinx Vivado)
• Experience with EDA tools for simulation, synthesis, place and route, and power analysis (e.g., ModelSim, Synopsys Design Compiler, Cadence Innovus, Synopsys PrimeTime)
• 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 ICCAD, DAC, ISCA, MICRO, HPCA, ISSCC, TinyML, IEDM, VLSI Symposium, ASPLOS, JSSC, TCAS
• Intent to return to the degree program after the completion of the internship/co-op