Research Scientist Intern, Experimentation (PhD)
Meta

Job Info

Meta was built to help people connect and share, and over the last decade, our tools have played a critical part in changing how people around the world communicate with one another. With over a billion people using the service and more than fifty offices around the globe, a career at Meta offers countless ways to make an impact in a fast growing organization.Meta is seeking Research Interns to join the Ads Experimentation org, where we strive to construct, identify, and measure the best personalized ads to people, maximizing their personal utility and advertiser value. We are committed to making fundamental advances in artificial intelligence and machine learning technologies that can be applied to all aspects of experimentation, including but not limited to, experimental designs, reinforcement learning, multi-armed bandits, active learning, off-policy evaluation, metric proxies, domain adaptation, and causal inference.Our interns closely collaborate with researchers and engineers within the organization and across the company (e.g., FAIR), push the boundaries of state-of-the-art research in AI and ML, share the latest findings through top-tier publications and open source, and integrate innovations at an unprecedented scale with massive and concrete impact every year.Our internships are twelve (12) to sixteen (16), or twenty-four (24) weeks long and we have various start dates throughout the year.

Research Scientist Intern, Experimentation (PhD) Responsibilities:

• Conduct state-of-the-art research to advance the state of the art in experimentation.
• Contribute to research that leads to innovations in scalable machine learning systems.
• Analyze and improve efficiency, scalability, and stability of corresponding deployed algorithms.
• Collaborate with researchers and engineers across diverse disciplines, including communicating research plans, progress, and results.
• Publish research results and contribute to research that can be applied to Meta product development.

Minimum Qualifications:

• Currently has or is in the process of obtaining a Ph.D. degree in Machine Learning, Artificial Intelligence, Computer Science, Information or Multimedia Retrieval, Reinforcement Learning, Optimization, Computational Statistics, Applied Mathematics, Physics, or related technical fields.
• Must obtain work authorization in the country of employment at the time of hire and maintain ongoing work authorization during employment.
• Experience with adaptive online and offline experimentation methods.
• Experience with Python, C++, C, Java, or other related languages.
• Experience with research and building systems based on machine learning and/or deep learning methods.

Preferred Qualifications:

• Intent to return to degree program after the completion of the internship/co-op.
• Proven track record of achieving significant research results as demonstrated by grants, fellowships, patents, as well as first-authored publications at leading workshops or conferences such as NeurIPS, ICML, ICLR, AAAI, KDD, IJCAI, AISTATS, UAI, RecSys, or similar.
• Demonstrated software engineer experience via an internship, work experience, coding competitions, or widely used contributions in open source repositories (e.g. GitHub).
• Demonstrated experience and self-driven motivation in solving analytical problems using quantitative approaches.
• Strong interest in theoretical and empirical research and for answering hard questions with research.
• Prior research in the domains of experimental designs, reinforcement learning, multi-armed bandits, active learning, off-policy evaluation, metric proxies, domain adaptation, or causal inference.
• Experience working and communicating cross functionally in a team environment.

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