机器人研究科学家实习生

Develop novel state-of-the-art algorithms for robot perception, manipulation, navigation, and control, leveraging modern deep learning and foundation-model techniques.

Train and evaluate robot learning policies — including imitation learning, reinforcement learning, and vision-language-action models — in simulation and on physical hardware.

Based on the project, help analyze and improve the efficiency, robustness, scalability, and real-time performance of algorithms deployed on robot platforms.

Perform research to advance the science and technology of intelligent machines.

Perform research that enables learning the semantics of multimodal and embodied data (images, video, depth, point clouds, tactile and force signals, proprioception, language, audio).

Contribute to data collection, teleoperation, and sim-to-real transfer pipelines that support large-scale robot learning.

Collaborate with researchers and cross-functional partners across hardware, controls, software, and product, including communicating research plans, progress, and results.

Publish research results and contribute to research that can be applied to Meta product development.

Currently has, or is in the process of obtaining a Ph.D. degree in Robotics, Computer Science, Computer Vision, Artificial Intelligence, Electrical/Mechanical Engineering, Controls, or a relevant technical field

Must obtain work authorization in 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 first-authored publications at leading workshops or conferences such as RSS, CoRL, ICRA, IROS, NeurIPS, ICML, ICLR, CVPR, ICCV, ECCV, or similar

Experience in advancing AI techniques for robotics or computer vision, including core contributions to open source robotics or ML libraries and frameworks (e.g.,

Experience deploying learned policies or perception systems on real robot hardware — manipulators, mobile robots, humanoids, or dexterous hands

Experience with classical robotics foundations: state estimation, SLAM, calibration, motion planning, and optimal or model-predictive control

Publications or experience in robot learning, reinforcement learning, machine learning, AI, computer vision, optimization, computer science, statistics, applied mathematics, or data science

Experience setting up ML or robot experiments and analyzing their results, including real-world evaluation protocols

Experience manipulating and analyzing complex, large scale, high-dimensionality data from varying sources and sensor modalities

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Individual compensation is determined by skills, qualifications, experience, and location.

Compensation details listed in this posting reflect the base hourly rate, monthly rate, or annual salary only, and do not include bonus, equity or sales incentives, if applicable.

In addition to base compensation, Meta offers benefits.

Learn more about benefits at Meta.

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Currently has, or is in the process of obtaining a Ph.D.

degree in Robotics, Computer Science, Computer Vision, Artificial Intelligence, Electrical/Mechanical Engineering, Controls, or a relevant technical field.

Experience with Python, C++, C, Java or other related language.