Postdoctoral Researcher, Central Applied Science, Forecasting (PhD)

Key Skills

Aartificial intelligence, Algorithms, Analytical and Problem solving, C Programming, C++, Design, Effective communication skills, Forecasting, Github, Mathematics, NeurIPS, Python Programming, PyTorch, TensorFlow

Job Description

Central Applied Science drives state-of-the-art scientific advancements for Meta's products and systems. The team's expertise spans many domains including AI/ML, statistics, economics, network science and mathematical optimization. We own tooling and libraries, develop methodologies, design and prototype solutions, and partner across Meta to launch these solutions so 3 billion people and 10 million advertisers can benefit. We seek Postdoctoral Researchers to focus on Forecasting. Applications for such work within Meta will span time intervals ranging from hours to years, and serve to improve Meta's products across Facebook, Instagram, WhatsApp, Messenger, and Reality Labs. Candidates should have a background in time-series analysis, forecasting of nonstationary and multivariate series, hierarchical reconciliation, modern machine learning methods as applied to forecasting problems, and counterfactual forecasting for causal inference. The ideal candidate will combine an interest in advancing the research frontier with a strong motivation to see their work implemented at scale in production systems.

Postdoctoral Researcher, Central Applied Science, Forecasting (PhD) Responsibilities

• Assess potential opportunities and execute world-class research associated with forecasting.
• Design and prototype new algorithms, optimization methods, and system architectures.
• Implement new algorithms or mechanisms, deploy them into internal or open-sourced libraries and tooling platforms, and conduct empirical studies on internal datasets to showcase value for real world applications.
• Publish research results in top-tier journals and at leading international conferences.
• Establish collaborations and communications externally with academia and industry.

Minimum Qualifications

• Currently has, or is in the process of obtaining a Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience. Degree must be completed prior to joining Meta.
• Currently has, or is in the process of obtaining, a PhD degree in Computer Science, Statistics, Mathematics, Economics or similar quantitative field. Degree must be completed prior to joining Meta.
• Understanding of modern machine learning techniques and their mathematical underpinning.
• Experience with AI methods for forecasting.
• Experience in communicating complex research both for public audiences of peers.
• Must obtain work authorization in the country of employment at the time of hire and maintain ongoing work authorization during employment.
• Experience in training, fine-tuning, and/or experimenting with foundation models beyond black-box use.
• Proficiency designing and implementing analytical and/or algorithmic solutions, tailored to particular business needs and tested on large data sets.
• Proficiency in Python.
• Familiarity with one or more deep learning frameworks (e.g. PyTorch, TensorFlow, etc.).

Preferred Qualifications

• Demonstrated software engineer experience via an internship, work experience, coding competitions, or widely used contributions in open source repositories (e.g. GitHub).
• Experience working and communicating cross-functionally in a team environment.
• 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, ICLR, AISTATS, and top economics, statistics, and operations research journals.
• Experience working in an industry applied research environment.
• Experience in training, fine-tuning, and/or experimenting with foundation models beyond black-box use.
• Proficiency in C or C++.
• Proficiency in causal inference.