Meta is seeking a Research Scientist to join Meta Fundamental AI Research (FAIR), a research organization focused on making significant progress in AI. Individuals in this role are expected to be recognized experts in identified research areas such as artificial intelligence, machine learning, robotics, and embodied AI, particularly including areas such as transfer learning, learning from demonstration, reinforcement learning, action-conditioned world models, perception, representation learning, robot control, navigation, mobile manipulation, dexterous manipulation, and vision-language models. You should have a keen interest in producing new, open science to make embodied agents more intelligent.Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience. PhD degree in the field of Artificial Intelligence, Robotics, Computer Vision, Machine Learning, Language, a related field, or equivalent practical experience. Experience with any of the following research areas: robotics, motion planning, embodied AI, human-robot interaction, sim-to-real transfer, learning from demonstration, reinforcement learning, dexterous manipulation, digital agents, vision language models, computer vision, egocentric perception, and/or LLMs. 2+ years of industry experience in relevant robotics related research areas, such as: robot learning, reinforcement learning, imitation learning, action-conditioned world models, task and motion planning, sim-to-real transfer robotic control, manipulation, navigation, or generally embodied AI. Must obtain work authorization in the country of employment at the time of hire and maintain ongoing work authorization during employment. 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), Computer Vision (CVPR, ICCV, ECCV). 5+ years of industry experience in relevant robotics related research areas, such as: robot learning, reinforcement learning, imitation learning, action-conditioned world models, task and motion planning, sim-to-real transfer robotic control, manipulation, navigation, or generally embodied AI. 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 with manipulating and analyzing complex, large scale, high-dimensionality data from varying sources. Experience building systems based on machine learning and/or deep learning methods. Experience with deep learning frameworks (such as pytorch, tensorflow) and Python. Experience solving complex problems and comparing alternative solutions, tradeoffs, and different perspectives to determine a path forward. Experience working and communicating cross functionally in a team environment. Experience with robotics frameworks like ROS, along with experience working with robot simulations and real-world hardware.