AI Research Scientist, Robotics

At Meta, we're building the future of human connection and the technology that enables it. This means continuously inventing and developing technologies for the next generation of experiences. To continue our efforts in the path to AGI, and as we move closer to a future with intelligent robots and advanced AI models, we're hiring talent across a broad range of disciplines from robotics hardware to system software and artificial intelligence. These crucial projects and initiatives taken on by this team have never been done before, so you have a rare opportunity to help us create new ways people connect around the world. We're seeking Research Scientists ready to use their skills in system design and modeling and with a knowledge of a wide variety of components and technologies. These roles will require research and problem-solving skills, as well as fabrication and prototyping to design, develop, and construct novel prototypes and architectures. These roles will work in a focused incubation team and collaborate with a large and wide-ranging set of scientists and engineers in the greater organization.

AI Research Scientist, Robotics Responsibilities:

• Perform fundamental and applied research to push the scientific and technological frontiers of embodied artificial intelligence
• Invent/improve novel data-driven paradigms for robotics, leveraging a variety of modalities (images, video, text, audio, tactile, etc)
• Investigate paradigms that can deliver a spectrum of embodied behaviors - from simulated characters to real robots, and from short-horizon, low-level to long-horizon, high-level intelligence
• Develop algorithms based on state-of-the-art machine learning and neural network methodologies
• Define, build and benchmark new functionalities needed for the next generation of AI
• Conduct research towards long-term product goals while identifying intermediate milestones
• Lead, plan, and execute novel research based on long-term objectives of the organization

• 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: VLM, 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

• Experience solving complex problems and comparing alternative solutions, tradeoffs, and different perspectives to determine a path forward.
• Experience working with robot simulations and real-world hardware.
• Experience working and communicating cross functionally in a team environment.
• 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.
• 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).
• 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.
• 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 deep learning frameworks (such as PyTorch, Tensorflow) and Python.