AI Research Scientist, Computer Vision – XR People Generation Full-time

The XR People Generation team works in collaboration with Reality Labs Research partners in order to deliver the future of communication – photorealistic telepresence via Codec Avatars. Our aspiration is to connect people separated by distance as if they were in the same room together. We achieve this by researching, developing and productionizing state-of-the-art methods in cross sections of computer graphics, computer vision and machine learning for human understanding and telepresence. These include (semi-) supervised deep learning, generative adversarial learning, active learning, neural rendering, depth sensing, 3D reconstruction, character animation and rendering.

AI Research Scientist, Computer Vision – XR People Generation Responsibilities

• Conduct applied research and develop novel, accurate AI algorithms and advanced systems for large scale applications
• Work on large initiatives or multiple projects of high complexity/scope and define clear long term objectives with short and medium term goals
• Collaborate with different cross functional teams in research and product sides
• Give technical research direction to the team as tech lead
• Mentor other researchers in the team
• Coding %: 70. System Design %: 30

Minimum Qualifications

• Bachelor’s degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience.
• PhD in Computer Science, Computer Engineering, or relevant technical field with 5+ years of experience
• Understanding of state-of-the-art full body human 3D reconstruction and 3D telepresence
• Led XFN groups across research and product towards meeting experiential and engineering targets
• Track record of delivering research into production, driving algorithmic changes towards on-device optimization
• Experience developing computer vision and machine learning algorithms in C/C++ and/or Python/PyTorch

Preferred Qualifications

• First-authored publications at peer-reviewed conferences (e.g. CVPR. ECCV, ICCV, NeurIPS, SIGGRAPH)
• Experience solving complex problems and comparing alternative solutions, tradeoffs, and diverse points of view to determine a path forward towards bringing state-of-the-art approaches onto real world devices
• Experience working and communicating cross functionally in a team environment
• Experience in machine learning infra systems
• Experience with CPU/GPU and mobile optimization

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