Research Scientist, Reinforcement Learning (PhD)

Meta's Monetization GenAI Model Capability Team is seeking a Research Scientist specializing in reinforcement learning to join their cutting-edge initiative. This role sits at the intersection of theoretical reinforcement learning and real-world applications in generative AI models for monetization purposes.

The position offers an exceptional opportunity to work with top researchers in applied reinforcement learning, conducting industry research on state-of-the-art algorithms. As part of Meta's top-priority MGenAI initiative, you'll be involved in customizing and tailoring GenAI models to meet specific business needs and drive value. The team's mission is to provide industry-leading, easy-to-use alignment algorithms for MGenAI applications.

The ideal candidate should have a PhD in Machine Learning, AI, or a related field, with strong programming skills in languages like Python and experience with deep learning frameworks such as PyTorch or TensorFlow. You'll be working closely with AI specialists to research and apply SOTA reinforcement learning algorithms on language models and diffusion models.

Key responsibilities include advancing machine learning and reinforcement learning technology, developing data-driven models of human behavior, and collaborating with cross-functional partners. You'll have the opportunity to contribute to publications and open-source efforts while applying your expertise to real-world applications at an unprecedented scale.

Meta offers a competitive compensation package ranging from $117,000 to $173,000 per year, plus bonus and equity opportunities. The company provides a collaborative environment where you'll work with leading researchers and have access to substantial computational resources. This role represents a unique opportunity to impact the future of AI technology while working at one of the world's leading tech companies.