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Job Details

Research Scientist Adaptive Experimentation PhD

Company name

Menlo Park, CA, United States

Employment Type

Sciences, Scientist, It, Research

Posted on
Jan 05, 2021

Valid Through
Apr 20, 2021

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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 Scientist to join the Adaptive Experimentation team. 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.Researcher will be expected to conduct cutting-edge applied research in the area of reinforcement learning and black-box optimization while working collaboratively with teams across the company to solve important problems. Research Scientists are expected to work alongside with applied statisticians specializing in causal inference and experimental design, so additional experience in these areas is a plus.

Required Skills:

Develop and apply new adaptive experimentation methods, such as multi-armed bandit optimization and reinforcement learning, to new and emerging applications

Minimum Qualifications:

Experience with developing and debugging in with Python with PyTorch, TensorFlow, Caffe, or related frameworks

Experience and a publication track record in at least one of the following: Deep reinforcement learning, Contextual bandits, AutoML, Bayesian optimization, or Evolutionary strategies or evolutionary algorithms

Currently has or is in the process of obtaining a Ph.D. degree in computer science, operations research, statistics, or related field

Must obtain work authorization in country of employment at the time of hire and maintain ongoing work authorization during employment

Preferred Qualifications:

An interest in disseminating new methods through open-source projects and/or academic publications.

First-author publications at peer-reviewed AI conferences (e.g. NIPS, ICML, ICLR, AISTATS, UAI).

Experience with causal inference, applied statistics, or A/B testing.

Industry: Internet

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

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