Improving Meta's products and infrastructure through scientific rigor and methodological innovation, addressing new opportunities and challenges across Meta, including the Meta family of apps
Requirements
- 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
- Currently has, or is in the process of obtaining, a PhD in Computer Science, Statistics, Machine Learning, Operations Research, or a related technical field
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
- 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
- Apply communication skills to engage diverse audiences on technical topics
Other
- Currently has, or is in the process of obtaining, a PhD in Computer Science, Statistics, Machine Learning, Operations Research, or a related technical field
- Must obtain work authorization in the country of employment at the time of hire and maintain ongoing work authorization during employment
- Intent to return to the degree-program after the completion of the internship/co-op
- Interpersonal experience: cross-group and cross-culture collaboration
- Experience working and communicating cross-functionally in a team environment
