Facebook Research Scientist, East Coast Computer Vision - ECCV (PhD) in Boston, Massachusetts
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.
This team supports research in AI for Computer Vision. The team is responsible for building the frameworks and tools that support research in this area as well as conducting research in collaboration with FAIR, product teams and other cross-functional teams. Computer Vision focuses on models and algorithms capable of performing recognition in images and videos, as well as generating and understanding images, videos and multimodal content. In this role, you will be responsible for performing cutting edge research on synthesis, recognition, detection etc., and develop experiments and prototypes at the frontier of AI Research. You will need to engage with research topics and cover new domains quickly; build deep expertise with Facebook data and tools; apply high standards to the research code around you and develop an ability to identify highly impactful projects in a complex and unexplored domain. You will gain valuable experience in artificial intelligence and AI, publish academic papers and help push forward the understanding of learning and intelligent systems.
Develop highly scalable algorithms based on state-of-the-art machine learning and neural network methodologies.
Collaborate with cross functional teams and scientists to facilitate research that enables learning the semantics of images, videos and other modalities.
Apply knowledge of relevant research domains along with expert coding skills to platform and framework development projects.
Adapt machine learning and neural network algorithms and architectures to best exploit modern parallel environments (e.g., distributed clusters, multicore SMP, and GPU) Suggestion:
Adapt machine learning and neural network algorithms and architectures to best exploit modern parallel environments (e.g., distributed clusters, multicore SMP, and GPU).
Currently has or is in the process of obtaining a PhD degree.
Research and/or work experience in artificial intelligence, machine learning, mathematics, and/or computer vision.
Coding experience in C, C++, Java, Python or similar language.
Must obtain work authorization in country of employment at the time of hire, and maintain ongoing work authorization during employment.
Research and software engineer experience demonstrated via an internship, work experience, coding competitions.
Research experience in metric learning, GAN, adversarial analysis, and/or manifold analysis.
First-authored publications at peer-reviewed conferences (e.g. CVPR, ECCV, ICCV, NeurIPS, or similar).
Equal Opportunity: Facebook 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, or other applicable legally protected characteristics. We also consider qualified applicants with criminal histories, consistent with applicable federal, state and local law. Facebook is committed to providing reasonable accommodations for candidates with disabilities in our recruiting process. If you need any assistance or accommodations due to a disability, please let us know at email@example.com.
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