Facebook Research Scientist, AI Research (PhD) in Menlo Park, California
Facebook'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 Facebook 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.
Facebook Reality Labs (FRL) is the world leader in the design of virtual and augmented reality systems. Come work alongside expert engineers and research scientists to create the technology that makes VR and AR pervasive and universal. Join the adventure of a lifetime as we make science fiction real and change the world.
We are seeking a Research Scientist to support development of state-of-the-art deep learning hardware components optimized for AR/VR systems. The successful candidate will be part of our efforts to architect, design and implement the hardware platforms for this activity and will be part of a team that includes algorithm, user experience, software, firmware and ASIC experts. The ideal candidate will understand the full stack from algorithms and architecture down to hardware accelerator blocks. This is a full-time position based in Menlo Park, CA.
Enable new user experiences in AR/VR via innovative applications of deep learning techniques for body tracking, user interface and other use-cases
Develop a system hardware design that includes camera image processing, neural nets and custom compute processing blocks which will surpass state-of-the-art metrics for compute resources, DRAM bandwidth and power consumption
Work with algorithm research teams to map CNN graphs to hardware implementations, model data-flows, create cost-benefit analysis and estimate silicon power and performance
Support all phases of Silicon SoC development from a deep learning perspective - from early definition on through specification, architecture, layout and production
Work with other groups to produce an FPGA test platform to test, develop and optimize the full system
Contribute to execution of our silicon technology/compute roadmap to make advances in performance, power consumption and form factor
Assess and recommend emerging technologies through partnerships with external suppliers
Employ the scientific method to evaluate performance and to debug, diagnose and drive resolution of cross-disciplinary system issues
Publish and present research at leading AI workshops and conferences
Currently has or is in the process of obtaining a PhD degree or completing a postdoctoral assignment in the field of Machine Learning, Artificial Intelligence, Computer Vision or similar
Available to start employment on or after February 1, 2019
Must obtain work authorization in country of employment at the time of hire, and maintain ongoing work authorization during employment
Experience in mobile SoC low-power design and architecture methodologies
Hands-on experience in deep learning algorithms and techniques, e.g., convolutional neural networks (CNN), recurrent networks (RNN) and/or related areas
Experience with custom SoC design especially as it relates to integration of hardware IP blocks, on-chip buses, DRAM bandwidth and power constraints
Software design and programming experience in C/C++ for development, debugging, testing and performance analysis
Interpersonal experience: cross-group and cross-culture collaboration
Experience in real-time processing for computer vision and user interaction tasks, high-compute/throughput systems and using simulation and modeling technique to estimate performance and power
Experience implementing deep neural networks for low-power SoC
Experience with industry trends and technologies for optimizing CNNs to reduce DRAM bandwidth requirement, on-chip storage and compute requirements
Proven track record of achieving results as demonstrated by grants, fellowships, patents, as well as first-authored publications at leading workshops or conferences such as ISSCC, VLSI Symposium, NIPS, ICML, CVPR, or similar
Equal Opportunity: Facebook is proud to be an Equal 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. Facebook 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@example.com.