Location
London

Hours
Full Time - Internship duration ranges from twelve (12) to twenty-four (24) weeks with various start dates throughout the year

Salary
Negotiable

About the Role
Meta Reality Labs Research (RL Research) brings together a world-class R&D team of researchers and engineers focused on advancing AI, Robotics, and AR/VR technologies. The Surreal Spatial AI group is seeking Research Scientist Interns to develop machine perception, 3D generative systems, and control technologies enabling robotic agents and AI systems to perceive, understand, reason about, and interact with the world.

As an intern, you will collaborate with research scientists and engineers on robot foundation models, including world action models (WAMs) and vision-language-action models (VLAs). Projects span multiple research streams such as exploring novel architectures, grounding models in 3D, learning action and goal representations, and integrating new sensor modalities like touch.

Responsibilities include performing fundamental and applied research at the intersection of multi-modal generative AI, predictive world modeling, embodied reasoning, and robotic manipulation. You will design and run empirical evaluations, write robust code for physical hardware and simulators, and contribute to publications and open-source releases.

This role offers a unique opportunity to work with cutting-edge technologies and contribute to open science that advances embodied intelligence in robotic agents.

Experience
- Currently pursuing or holding a PhD in Computer Vision, Robotics, Machine Learning, Artificial Intelligence, Computer Science, or a related STEM field
- Research experience in robotics, 3D computer vision, deep learning (including multimodal or 3D generative modeling), predictive world models, scene understanding, egocentric perception, learning from demonstration, reinforcement learning, or learning-based robotic control
- Proficiency with deep learning frameworks such as PyTorch or TensorFlow and Python programming
- Experience with physics simulation platforms (e.g., Isaac Sim, Isaac Lab, MuJoCo)
- Hands-on experience with real robot hardware beyond simulation, including data collection, debugging, or deploying learned policies
- Experience training or evaluating large-scale robot foundation models (e.g., VLAs, WAMs), world models, or generative video models
- Expertise in applying 3D computer vision to embodied AI, such as 3D scene understanding, reconstruction, or 3D-aware policies and world models
- Experience with action or goal representation learning, such as latent action models or goal-conditioned policy learning
- Experience integrating tactile, force/torque, or other non-visual sensing into robot learning
- Familiarity with reinforcement learning, long-horizon planning, kinematics, or sim-to-real transfer
- Demonstrated research and software engineering skills through internships, work experience, coding competitions, or significant open source contributions
- Proven track record of impactful results demonstrated by grants, fellowships, patents, or publications at leading conferences or journals (e.g., CVPR, ICCV, ECCV, NeurIPS, ICML, ICLR, CoRL, RSS, ICRA, IROS)

About you
- Strong interest in producing new, open science to advance embodied intelligence in agents
- Ability to collaborate effectively across groups and cultures
- Excellent communication skills for sharing research with peer audiences
- Must be authorized to work in the country of employment at the time of hire and maintain ongoing work authorization
- Intent to return to your degree program after completing the internship
- Ability to commit to 24 consecutive weeks for the internship

Qualifications
- PhD candidate or graduate in a relevant STEM field
- Proficiency in Python and deep learning frameworks
- Experience with robotics, computer vision, machine learning, and AI research methodologies