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 either our Redmond, WA or Menlo Park, CA offices.
* Enable new user experiences in AR/VR via innovative applications of deep learning techniques for body tracking, user interface and other use-cases
Develop system hardware design that includes camera image processing, neural nets and custom compute processing blocks. Such design 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
* 2+ years of experience and PhD in Computer Science, Electrical Engineering or equivalent field
Experience in mobile SoC low-power design and architecture methodologies
Experience in deep learning algorithms and techniques, e.g., convolutional neural networks, recurrent networks, etc.
Knowledge of custom SoC design especially 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
Experience crossing multi-disciplinary boundaries to drive optimal system solutions
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