Core Data Science Intern, Adaptive Experimentation Research (PhD)
- Menlo Park, CA
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.
Facebook is seeking research interns to join the Adaptive Experimentation team within CDS (Core Data Science). The mission of the team is to do cutting-edge research and build new tools for reinforcement learning and black-box optimization that democratize new and emerging uses of AI technologies across Facebook, Instagram, and sister companies. Applications range from AutoML, to automating A/B tests, to contextual decision-making for mobile and server-side infrastructure, to black-box optimization for hardware design.
- Develop and apply new adaptive experimentation methods, such as multi-armed bandit optimization and reinforcement learning, to new and emerging applications.
- Currently has or is in the process of obtaining a Ph.D. degree in computer science, operations research, statistics, or related field
- Experience with developing and debugging in with Python with PyTorch, TensorFlow, Caffe, or related frameworks
- Research experience and a publication track record in at least one of the following,Deep reinforcement learning, Contextual bandits, AutoML, Evolutionary strategies, evolutionary algorithms or Bayesian optimization
- Must obtain work authorization in country of employment at the time of hire and maintain ongoing work authorization during employment
- Must be currently enrolled in a full-time degree program and returning to the program after the completion of the internship/co-op
- A passion for disseminating new methods through open-source projects and/or academic publications
- Experience with causal inference, applied statistics, or A/B testing
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