AI Research Scientist, Robotics: Meta

Meta is seeking a Research Scientist to join its team building the future of human connection through embodied artificial intelligence. As Meta moves closer to a future with intelligent robots and advanced AI models, this role offers a rare opportunity to help create new ways for people to connect around the world.

As part of a focused incubation team, you will be responsible for designing, developing, and constructing novel prototypes and architectures. Your work will involve fundamental and applied research to push the scientific and technological frontiers of robotics and embodied AI, collaborating with a large and diverse set of scientists and engineers across the organization.

Key Responsibilities:
Perform fundamental and applied research to advance the state-of-the-art in embodied artificial intelligence.

Invent and improve novel data-driven paradigms for robotics, leveraging various modalities (images, video, text, audio, tactile, etc.).

Investigate and develop paradigms that can deliver a spectrum of embodied behaviors, from simulated characters to real robots.

Develop algorithms based on state-of-the-art machine learning and neural network methodologies.

Lead, plan, and execute novel research based on the long-term objectives of the organization.

Minimum Qualifications:
A Bachelor's degree in Computer Science, Computer Engineering, or a relevant technical field.

A PhD degree in Artificial Intelligence, Robotics, Computer Vision, Machine Learning, or a related field (or equivalent practical experience).

2+ years of industry experience in relevant robotics research areas such as robot learning, reinforcement learning, imitation learning, or embodied AI.

Experience with research areas like motion planning, human-robot interaction, sim-to-real transfer, or vision language models.

Must be able to obtain and maintain work authorization in the country of employment.

Preferred Qualifications:
5+ years of industry experience in relevant robotics research areas.

A proven track record of achieving significant results, as demonstrated by publications at leading conferences (e.g., NeurIPS, ICML, ICRA, CoRL, CVPR).

Experience working with both robot simulations and real-world hardware.

Experience building systems based on deep learning methods using frameworks like PyTorch or TensorFlow.