Meta AR/VR Job | Research Engineer Intern, Computer Vision & Machine Learning, XR People (PhD)
Job（岗位）: Research Engineer Intern, Computer Vision & Machine Learning, XR People (PhD)
Type（岗位类型）: Computer Vision | Research
Citys（岗位城市）: Zurich, Switzerland
Date（发布日期）: Before 2021-12-14
Summary（岗位介绍）
The Facebook Reality Labs (FRL) organization at Facebook is helping more people around the world come together and connect through world-class Augmented and Virtual reality (AR/VR) products. With global departments dedicated to research and development in computer vision, machine learning, haptics, social interaction, and more, FRL is committed to driving the state of the art forward through relentless innovation. The potential to change the world is immense – and we’re just getting started.
Augmented and Virtual reality will transform the way people come together to work and play. By developing new hardware and software products capable of understanding human appearance, movement and expression, we aim to make it possible for people to feel like they are directly in front of each other, despite being separated by vast distances.
Our XR People organization in Zurich is focused on research and development of machine perception technologies from early concepts to production level across all of Facebook’s AR/VR products and surfaces including Oculus products and Family of Apps (Facebook, Instagram, Messenger, WhatsApp). We develop core capabilities across a range of product domains including Avatars, AR/VR remote presence / calling, AR Commerce, AR Sharing, and more.
As a PhD intern at Facebook Reality Labs (FRL), you will be researching and developing state of the art computer vision and machine learning technologies for solving challenges that bridge virtual and real worlds and can impact billions of people. The ideal candidate is pursuing a PhD in computer vision or machine learning research fields, and is passionate about exploring and applying semi-supervised learning methods in the context of human body tracking.
It is early days and we’re looking for you to usher in the next era of human – human and human – computer interaction by solving these problems together with us.
Qualifications（岗位要求）
Currently has, or is in the process of obtaining, a PhD degree in Computer Science, Electrical Engineering, or Electrical and Computer Engineering in the field of computer vision, machine learning, computer graphics, or robotics.
3+ years experience in C++ and Python.
2+ years experience with building systems based on computer vision and deep learning methods for object detection, objection recognition, keypoint estimation, or segmentation.
Proven track record of achieving significant results as demonstrated by publications in top computer vision conferences (e.g., CVPR, ICCV, ECCV, or, SIGGRAPH) or journals (e.g., IEEE Transactions on Pattern Analysis and Machine Intelligence, International Journal of Computer Vision, Pattern Recognition, or IEEE Transactions on Image Processing).
Must obtain work authorization in the country of employment at the time of hire and maintain ongoing work authorization during employment.
Description（岗位职责）
Investigate, design and develop novel computer vision and machine learning algorithms in areas such as segmentation, face tracking, body tracking, key point estimation, depth sensing, generative approaches such as GANs, 3D stereo and volumetric reconstruction, avatars, reconstructions and virtual try-ons.
Collaborate with and support other research scientists and engineers across various disciplines
Develop tools, scripts and tests to support your project.
Document and present your progress and project.
Additional Requirements（额外要求）
Research experience on prototyping and engineering in at least ONE relevant specialization area in Computer Vision or Machine Learning: generative models such as GANs / pose estimation and dense 3D reconstruction / object detection, segmentation and tracking / scene understanding / photorealistic rendering.
Demonstrated software engineer experience via an internship, work experience, coding competitions, or widely used contributions in open source repositories (e.g. Github).
Ability to communicate complex research in a clear, precise, and actionable manner.
Intent to return to degree-program after the completion of the internship/co-op.
