Applied Research Scientist, Computer Vision
Facebook's mission is to give people the power to build community and bring the world closer together. Through our family of apps and services, we're building a different kind of company that connects billions of people around the world, gives them ways to share what matters most to them, and helps bring people closer together. Whether we're creating new products or helping a small business expand its reach, people at Facebook are builders at heart. Our global teams are constantly iterating, solving problems, and working together to empower people around the world to build community and connect in meaningful ways. Together, we can help people build stronger communities â€" we're just getting started.
We are seeking world-class computer vision experts to join our teams in developing next generation products and platforms doing research and engineering at scale. We're applying cutting-edge computer vision algorithms to a wide range of media understanding challenges at Facebook.
- Develop novel and accurate computer vision algorithms and systems, leveraging deep learning and machine learning on big data resources.
- Analyze and improve efficiency, scalability, and stability of various deployed systems.
- Collaborate with team members from the level of prototyping to the level of production.
- 5+ years of experience in building, leading and specializing in commercial computer vision projects from the level of researching a prototype to the level of production.
- Experience in C/C++ and Python rapid programming on Linux OS.
- Experienced with training deep neural networks for key computer vision tasks such as classification, semantic segmentation, object detection, etc.
- Experience with one or more deep learning frameworks such as PyTorch, TensorFlow, Caffe2.
- Software engineering experience with knowledge of the software lifecycle that includes testing, version control and shipping high quality code.
- PhD/MS with experience in Computer Science with published projects in the fields of machine learning, deep learning and/or computer vision.
- Candidates with experience developing novel algorithms in the following will be given extra consideration.
- - Deep adversarial networks, image and video forensics.
- - Cross domain adaptation for rapid model transfer across domains.
- - Transfer learning including zero shot learning, attribute learning, and knowledge graphs.
- - Deep graphical modeling.
- - Explainability in computer vision and AI such as image and video captioning, and causal reasoning.
- Experienced with the development of enterprise level AI, machine learning and deep learning platform involving big data management and GPU compute.
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