Degree must be completed prior to joining Meta Bachelor's or Master's degree in Computer Science, Machine Learning, or a related technical field 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 Experience with machine learning models, and frameworks such as PyTorch, TensorFlow, etc Proficiency in programming languages such as Python, C++, or similar 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) 1+ years of experience in robotics or related field, or advanced degree with equivalent experience Experience designing and developing new robotic systems, platforms or infrastructure Experience with robotics frameworks like ROS, along with experience working with robot simulations and real-world hardware Experience with manipulating and analyzing complex, large scale, high-dimensionality data from varying sources Experience solving complex problems and comparing alternative solutions, trade-offs, and diverse points of view to determine a path forward Experience working and communicating cross functionally in a team environment Experience building systems based on machine learning and/or deep learning methods PhD degree in computer science, robotics, AI, or related fieldsMeta builds technologies that help people connect, find communities, and grow businesses. Individuals in this role are proficient 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.