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

About Central Applied Science

Central Applied Science is a research and development team focused on improving Meta’s products and infrastructure. We generate real-world impact through scientific rigor and methodological innovation, addressing foundational opportunities and challenges across Meta, including the Meta family of apps that enable billions of people to communicate daily.

The group is interdisciplinary, with expertise spanning artificial intelligence, machine learning, statistics, economics, and operations research. This diversity enriches our research and expands the scope and scale of projects. We deliver value through collaborative projects with other Meta groups and the academic community, and we build and open-source technical products aligned with our areas of expertise.

Internship Overview

We seek research science interns to join our team. The ideal candidate will have extensive graduate training in a core scientific field, 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 sixteen (16) to twenty-four (24) weeks long, designed to allow interns to advance into production and author papers for leading conferences and workshops. Start dates occur at various times throughout the year.

Responsibilities

• Answer important product and business questions by applying appropriate scientific methodologies, and develop new methodologies when necessary.
• Synthesize and apply insights from relevant academic literatures to Meta’s products.
• Communicate effectively to engage diverse audiences on technical topics.
• Work 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 product or infrastructure improvements.

Qualifications

• Currently pursuing or holding a PhD in Computer Science, Statistics, Machine Learning, Operations Research, or a related technical field.
• Expertise in empirical research, including manipulating and analyzing complex data and communicating quantitative analyses.
• Proficiency with 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.
• Strong interpersonal skills and experience collaborating across groups and cultures.
• Must obtain work authorization in the country of employment at the time of hire and maintain ongoing work authorization during employment.
• A proven track record of significant results demonstrated by grants, fellowships, patents, or first-authored publications at leading workshops or conferences (e.g., NeurIPS, ICML, KDD, AISTATS, ICLR).
• Experience working and communicating cross-functionally in a team environment.
• Intent to return to the degree program after completing the internship.