Research Scientist Intern, Optimization, Privacy and Inference (PhD)
Meta

Central Applied Science is a research and development team, working to improve Meta's products and infrastructure. We generate real-world impact through a combination of scientific rigor and methodological innovation. Our focus is on foundational work that addresses new opportunities and challenges across Meta, including the Meta family of apps that enable billions of people to communicate with each other daily.Central Applied Science is interdisciplinary, with expertise in many fields including artificial intelligence, machine learning, statistics, economics, and operations research. This diversity enriches our research and expands the scope and scale of projects we can address. We deliver value through collaborative projects with other groups at Meta and with the academic community. In addition, we build and open-source technical products aligned with our areas of expertise.We seek research science interns to join our team. The ideal candidate will have extensive graduate training in one of our core scientific fields, prior experience developing applied solutions, and an interest in tackling challenging, open-ended issues to improve Meta's products and systems with real-world impact.Our internships are twelve (12) to twenty-four (24) weeks long and we have various start dates throughout the year.

Research Scientist Intern, Optimization, Privacy and Inference (PhD) Responsibilities:

• Answer important product and business questions, by applying appropriate scientific methodologies, and developing new methodologies when necessary.
• Synthesize and apply insights from the relevant academic literatures to Meta's products.
• Apply communication skills to engage diverse audiences on technical topics.
• Work both independently and collaboratively with other scientists, engineers, and product teams to accomplish complex tasks that create value for Meta's community of over 3.5 billion users.
• Identify new areas across Meta's family of apps and products where scientific insights can drive improvements in product or infrastructure.

Minimum Qualifications:

• Currently has, or is in the process of obtaining, a PhD in Computer Science, Statistics, Machine Learning, or a related technical field.
• Expertise in empirical research, including manipulating and analyzing complex data and communicating quantitative analyses.
• Knowledge of common programming languages such as Python or C++, strong development capabilities, and familiarity with software engineering best practices.
• Experience using machine learning and deep learning frameworks, such as PyTorch or scikit-learn.
• Interpersonal experience: cross-group and cross-culture collaboration.
• Must obtain work authorization in the country of employment at the time of hire and maintain ongoing work authorization during employment.

Preferred Qualifications:

• Proven track record of achieving significant results as demonstrated by grants, fellowships, patents, as well as first-authored publications at leading workshops or conferences such as NeurIPS, ICML, KDD, AISTATS or ICLR.
• Experience working and communicating cross-functionally in a team environment.
• Intent to return to the degree-program after the completion of the internship/co-op.

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