Fundamental AI Research Scientist, Physical World Models, FAIR

Meta is seeking a Research Scientist to join the Fundamental AI Research (FAIR) team, one of the top industrial AI research organizations in the world. Come join FAIR's efforts to build world models, learning to understand and make predictions about the physical world, especially from video, and develop efficient algorithms for world model-based planning and control.

Our team is driving an ambitious agenda to train and use world models for embodied and wearable agents. We innovate across related topics including self-supervised learning from video (e.g., joint-embedding predictive architectures/JEPAs), predictive models, model-based reinforcement learning and model-predictive control. We accomplish this by advancing research across the stack, including data curation, training large-scale state-of-the-art models, and designing robust benchmarks. We are looking for Research Scientists who share our passion for building efficient, scalable, and robust models of the world that will be part of the next paradigm in AI models.Fundamental AI Research Scientist, Physical World Models, FAIR Responsibilities

• Leading, collaborating, and executing on research that pushes forward the state of the art in artificial intelligence
• Performing research that enables learning the semantics of data (images, video, text, audio, and other modalities)
• Working towards long-term research goals, while identifying immediate milestones
• Influencing progress of relevant research communities by producing publications
• Collaborating with scientists and engineers in a large cross-functional team
• Open source high quality code and produce reproducible research

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
• PhD degree in AI, computer science, data science, or related technical fields
• First-authored publications at peer-reviewed conferences, such as ICML, NeuRIPS, ICLR, CVPR, ICCV, CoRL, or similar
• Research background in machine learning, artificial intelligence, computational statistics, applied mathematics, or related areas
• Experience coding software and executing complex experiments
• Experience with Python and PyTorch

Preferred Qualifications

• 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 publications at leading workshops, journals or conferences in Machine Learning (NeurIPS, ICML, ICLR), Robotics (ICRA, IROS, RSS, CoRL), and Computer Vision (CVPR, ICCV, ECCV).
• Experience solving complex problems and comparing alternative solutions, tradeoffs, and different perspectives to determine a path forward.
• Experience collaborating in a team environment on research projects
• Experience building systems based on machine learning and/or deep learning methods.
• Experience with manipulating and analyzing complex, large scale, high-dimensionality data from varying sources.

For those who live in or expect to work from California if hired for this position, please click here for additional information. About Meta Meta builds technologies that help people connect, find communities, and grow businesses. When Facebook launched in 2004, it changed the way people connect. Apps like Messenger, Instagram and WhatsApp further empowered billions around the world. Now, Meta is moving beyond 2D screens toward immersive experiences like augmented and virtual reality to help build the next evolution in social technology. People who choose to build their careers by building with us at Meta help shape a future that will take us beyond what digital connection makes possible today—beyond the constraints of screens, the limits of distance, and even the rules of physics.
US$117,000/year to US$173,000/year + bonus + equity + benefits

Individual compensation is determined by skills, qualifications, experience, and location. Compensation details listed in this posting reflect the base hourly rate, monthly rate, or annual salary only, and do not include bonus, equity or sales incentives, if applicable. In addition to base compensation, Meta offers benefits. Learn more about