Applied Research Manager (Mobile Vision Zurich)

AR/VR | Zurich, Switzerland

The Facebook Reality Labs (FRL) organization at Facebook is helping 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. The Mobile Vision team is seeking world-class computer vision experts to join the team in developing next generation products and platforms doing research and engineering at scale. Our mission is to advance the state-of-the-art in computer vision algorithms for on-device computer vision. In this role, you will both manage and partner with groups working across the full spectrum from research to product development supporting multiple product lines. You will oversee research investments comprising state-of-the-art deep learning algorithms for computer vision, spanning areas including but not limited to generative methods (such as GANs, photorealistic rendering), deep learning model optimization (such as pruning, quantization and neural architecture search), semantic understanding (such as object detection and pose estimation, video summarization), 3D geometry understanding (such as deep local features), and human understanding (such as human body pose estimation, action recognition). You will also be responsible for developing longer-term research and technical strategies in collaboration with key partners. Prospective candidates should have sufficient research depth and breadth in the associated set of technologies to make portfolio management, resourcing, and roadmap decisions.


  • Leading an organization of applied research scientists from research across development and integration of advanced systems relying heavily on Computer Vision and Machine Learning technologies
  • Engaging cross-functionally with other researchers and engineers to develop concepts that advance the entire product pipeline across hardware, software, integration, infrastructure, and applications
  • Recruit world-class talent and provide mentorship to team members
  • Working closely with various organizations to define and execute the long-term strategies and roadmaps
  • Developing and communicating technology development strategies and status
  • Facilitating and working with the team to proactively alleviate project bottlenecks

Minimum Qualifications

  • PhD degree in Computer Science or equivalent experience
  • Experience of building and managing high-performance teams in multi-disciplinary global organizations at the intersection of research and product
  • Experience supporting an applied research organization through technical leadership
  • Experience in recruiting and managing technical teams comprised of Computer Vision and Machine Learning scientists and engineers
  • Experience in managing teams productizing Computer Vision and Deep learning technologies from conception
  • Experience in leading teams and projects in one or more of the technical domains of machine perception (i.e., efficient deep learning, GANs)
  • Leadership and interpersonal communication experience in working across many disciplines, drive best practices, and mentor team members)
  • Experience managing joint hardware-software development and associated rapid prototyping projects

Preferred Qualifications

  • Experience in leading teams developing social presence technologies such as generative methods, deep learning model optimization, semantic understanding, 3D geometry understanding, and human understanding
  • Experience in leading teams interfacing with HW (sensors, silicon) teams in setting requirements and product tradeoffs
  • Flexibility and resilience in a dynamic environment

Ready to Join?

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Oculus 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, genetic information, or other applicable legally protected characteristics. We also consider qualified applicants with criminal histories, consistent with applicable federal, state and local law.

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