Research Scientist, Reinforcement Learning (PhD)

The Monetization GenAI Model Capability Team is responsible for all reinforcement learning applications across Monetization GenAI. We conduct state-of-the-art industry research in reinforcement learning to bridge the gap between theoretical reinforcement learning and real-world problems in generative AI models for monetization purpose. At Meta, MGenAI is a top-priority company initiative that requires the customization of off-the-shelf GenAI models. This involves significant investment to tailor these models to meet our specific needs and drive business value. Our mission is to provide industry-leading, easy-to-use and effective alignment algorithms for MGenAI applications. In this role, you will be working closely with our AI specialist to research and apply SOTA reinforcement learning algorithms on language models and diffusion models.We are seeking Research Scientists to help us with a mission to bring reinforcement learning to large scale real-world GenAI applications. Our Research Scientists have an opportunity to work with top researchers in applied reinforcement learning to conduct industry research on reinforcement learning algorithms with a goal to achieve a better algorithm, design an algorithm in real-world applications, and apply their ideas at an unprecedented scale.

• Perform research to advance the science and technology of machine learning and reinforcement learning.
• Devise better data-driven models of human behavior.
• Collaborate with researchers and cross-functional partners including communicating research plans, progress, and results.
• Apply state of the art reinforcement learning technologies to achieve production impact in GenAI applications.
• Contribute to publications and open-sourcing efforts.

• 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 in the field of Machine Learning, Artificial Intelligence, Computer Science, Information or Multimedia Retrieval, Reinforcement Learning, Mathematics, a related field, or equivalent practical experience. Degree must be completed prior to joining Meta.
• Experience in Python, C++, Java or other related language
• Experience with Deep Learning frameworks such as Pytorch or Tensorflow
• Must obtain work authorization in the country of employment at the time of hire, and maintain ongoing work authorization during employment.

• Experience with reinforcement learning in applied areas beyond simple simulators.
• Demonstrated experience in solving analytical problems using quantitative approaches.
• Experience manipulating and analyzing complex, high-volume, high-dimensionality data from varying sources.
• Experience building systems based on machine learning, reinforcement learning and/or deep learning methods.
• 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, ICLR, AAAI, RecSys, KDD, IJCAI, CVPR, ECCV, ACL, NAACL, EACL, ICASSP, or similar.
• Demonstrated research and software engineering 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.
• Experience solving complex problems and comparing alternative solutions, tradeoffs, and diverse points of view to determine a path forward.