Lead, collaborate, and execute on research that pushes forward the state of the art in world modelling and artificial intelligence Perform research that enables learning the semantics of data across modalities including images, video, text, and audio Work towards long-term research goals while identifying immediate milestones Develop and evaluate novel architectures and training methods for learning predictive models of visual, physical, or multimodal environments Explore applications of world models to planning, prediction, control, and decision-making for embodied agents Influence progress of relevant research communities by producing publications at peer-reviewed venues Collaborate with scientists and engineers in a large cross-functional team Open source high quality code and produce reproducible research Support recruiting efforts by engaging with potential candidates and sharing insights about world modelling research at MetaBachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience Currently has, or is in the process of obtaining, a PhD degree in AI, computer science, data science, robotics, or related technical fields First-authored publications at peer-reviewed conferences such as ICML, NeurIPS, ICLR, CVPR, ICCV, CoRL, RSS, or ICRA, or similar Research background in machine learning, artificial intelligence, robot learning, computational statistics, applied mathematics, or related areas Experience coding software and executing complex experiments Experience with Python and PyTorch Experience solving complex problems and comparing alternative solutions, tradeoffs, and different perspectives to determine a path forward Track record of achieving significant results as demonstrated by grants, fellowships, patents, or publications at leading conferences in Machine Learning (NeurIPS, ICML, ICLR), Robotics (ICRA, IROS, RSS, CoRL), or Computer Vision (CVPR, ICCV, ECCV) Experience with self-supervised learning from video, predictive models, model-based reinforcement learning, or model-predictive control Experience building systems based on machine learning or deep learning methods Experience manipulating and analyzing complex, large-scale, high-dimensionality data from varying sources Experience collaborating in a team environment on research projectsMeta builds technologies that help people connect, find communities, and grow businesses. 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.