Applied Research Scientist, Video Understanding
(New York, NY)
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 - we're just getting started.
Every day, massive amounts of video are uploaded into Facebook's services. In order to serve our communities better, it is critical that we can understand this content; think about being able to answer questions like "This person will like this video because...." or "This person will find this video inappropriate because..." Our goals broadly encompass content understanding, including the ability to produce video summaries, categorize content according to topic and purpose, identify audio events, find key-frames, and do keyword spotting. To achieve these goals, we are building a Video Understanding team in New York City, that will engage in a multidisciplinary effort combining speech recognition, natural language processing, and image processing. We view video as inherently multi-modal content, and seek to develop methods that use all the information available. We are looking for researchers in machine learning and AI with strong software engineering skills, and a desire to build systems that will ship to billions of people. The Video Understanding Team is part of the Applied Machine Learning organization. The team carries out applied research in ML/AI and designs, develops and deploys state of the art ML/AI algorithms to the rest of Facebook. Our algorithms are used for ranking, improving content integrity, keeping communities safe, and power multiple product experiences across Facebook, Messenger, Instagram, WhatsApp and Oculus.
- Develop highly scalable algorithms based on state-of-the-art machine learning and neural network methodologies
- Conduct research to advance the state-of-the-art, and publish work in relevant speech, NLP, and machine learning conferences and journals
- Apply expert coding skills to projects in partnership with other engineers across research, product, and infrastructure teams
- Adapt machine learning and neural network algorithms for training competitive, state-of-the-art models which make the best use of modern parallel environments (e.g. distributed clusters, GPU)
- MS degree in Computer Science or related quantitative field with 5+ years of work experience, or Ph.D. degree in Computer Science or related quantitative field
- Knowledge of machine learning, neural networks, and deep learning
- Experience building systems based on machine learning and/or deep learning methods, especially in the areas of speech recognition, natural language processing, image processing, or other machine-perception tasks
- Experience developing and debugging in C/C++ and/or Python
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