Meta AR/VR Job | Research Scientist, 3D Computer Vision and Machine Perception (PhD)
Job（岗位）: Research Scientist, 3D Computer Vision and Machine Perception (PhD)
Type（岗位类型）: 3D Product Design | Computer Vision, Machine Learning, Research
Citys（岗位城市）: Redmond, WA
Date（发布日期）: 2022-1-27
Summary（岗位介绍）
Reality Labs brings together a world-class team of researchers, developers, and engineers to create the future of virtual and augmented reality, which together will become as universal and essential as smartphones and personal computers are today. And just as personal computers have done over the past 45 years, AR and VR will ultimately change everything about how we work, play, and connect. We are developing all the technologies needed to enable breakthrough AR glasses and VR headsets, including optics and displays, computer vision, audio, graphics, brain-computer interface, haptic interaction, eye/hand/face/body tracking, perception science, and true telepresence. Some of those will advance much faster than others, but they all need to happen to enable AR and VR that are so compelling that they become an integral part of our lives.
Reality Labs Research (RL Research) brings together a world-class R&D team of researchers, developers, and engineers with the shared goal of developing AR and VR across the spectrum. The Surreal Vision group at RL Research is seeking exceptional research scientists to solve the next generation of research challenges on the path to building future machine perception enabled technologies. The aim of this role is to develop and advance computer vision algorithms and SW systems for real-time and offline SLAM, visual odometry, localization, 3D reconstruction, and object understanding.
Qualifications（岗位要求）
Currently has, or is in the process of obtaining a Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience. Degree must be completed prior to joining Meta.
Background in advanced geometric computer vision, including tracking, SLAM, visual-inertial odometry, state estimation, mapping, object understanding, scene reconstruction, or relocalization technologies.
Background in mathematics and understanding of numerical optimization, linear algebra, probabilistic estimation and 3D geometry.
5+ years experience with a mastery of modern features in C++ or Python.
Experience designing machine learning algorithms, including experience creating software for data loading, training, and inference of novel ML architectures.
Experience with ML frameworks such as PyTorch.
Experience understanding, developing, and analyzing complex systems.
Must obtain work authorization in 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 in the field of computer vision, robotics, relevant technical field, or equivalent practical experience. Degree must be completed prior to joining Meta.
Description（岗位职责）
Research, develop and prototype advanced software technologies in the domain of tracking, 3D reconstruction, localization, object detection, and scene understanding.
Analyze and improve efficiency, accuracy, scalability, and stability of currently deployed systems.
Collaborate with team members throughout the lifetime of a project, from prototyping to deployed products.
Deliver research results that have a direct impact on Meta products.
Additional Requirements（额外要求）
Experience with SLAM systems e.g. monocular, stereo, visual-inertial or RGBD.
Experience with hand, arm, or wrist detection and tracking systems.
Background in optics or computational imaging.
Experience working in a Linux environment.
Broad understanding of the full machine vision pipeline from sensors to high-level algorithms.
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 CVPR, ECCV/ICCV, BMVC, ICRA, IROS, or SIGGRAPH.
Demonstrated software engineer experience via an internship, work experience, coding competitions, or widely used contributions in open source repositories (e.g. GitHub.).
Experience solving complex problems and comparing alternative solutions, tradeoffs, and diverse points of view to determine a path forward.
Experience working and communicating cross functionally in a team environment.
