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AI Research Scientist, Robotics

Job in Burlingame, San Mateo County, California, 94012, USA
Listing for: Meta
Full Time position
Listed on 2025-12-27
Job specializations:
  • Engineering
    Robotics, Artificial Intelligence, AI Engineer
  • Research/Development
    Robotics, Artificial Intelligence, Data Scientist
Job Description & How to Apply Below

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This range is provided by Meta. Your actual pay will be based on your skills and experience — talk with your recruiter to learn more.

Base pay range

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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, machine perception, 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 a Research Scientist 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 functionality 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.
Minimum Qualifications
  • 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 Large Language Models.
  • 5+ years of industry experience in relevant robotics‑related research areas, such as Vision Language Models 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.
Preferred Qualifications
  • Proven track record of achieving significant results as demonstrated by grants, fellowships, patents, and publications at leading workshops, journals or conferences in Machine Learning (NeurIPS, ICML, ICLR), Robotics (ICRA, IROS, RSS, CoRL), Computer Vision (CVPR, ICCV, ECCV).
  • 7+ 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. Git Hub).
  • Experience with manipulating and analyzing complex, large‑scale, high‑dimensionality data from varying sources.
  • Experience building systems based on machine learning…
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