Role overview
Meta builds technologies that help people connect, find communities, and grow businesses. When Facebook launched in 2004, it changed the way people connect. Apps like Messenger, Instagram and WhatsApp further empowered billions around the world. Now, Meta is moving beyond 2D screens toward immersive experiences like augmented and virtual reality to help build the next evolution in social technology. People who choose to build their careers by building with us at Meta help shape a future that will take us beyond what digital connection makes possible today—beyond the constraints of screens, the limits of distance, and even the rules of physics.
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.
What you'll work on
- Lead, collaborate, and execute on research that pushes forward the state of the art in 3D computer vision, embodied reasoning, and/or predictive world modeling
- Directly contribute to experiments, including designing experimental details, authoring reusable code, running evaluations, and organizing results
- Work with the team to design practical experiments and prototype systems related to dynamic scene modeling, long-horizon reasoning, and machine perception
- Contribute to publications and open-sourcing efforts
- Help identify long-term ambitious research goals as well as intermediate milestones
What we're looking for
- Hands-on experience implementing 3D computer vision algorithms and training/evaluating large-scale ML/AI models
- Familiarity with Reinforcement Learning (RL), VLAs, control theory, or learning-based planning
- Experience bridging the gap between perception and action (e.g., Active Vision, Embodied AI, Inverse RL, or RLHF)
- Experience with physics simulators or synthetic environments (e.g., Habitat, MuJoCo, Isaac Lab)
- Experience working in a Unix environment
- Demonstrated research and software engineering experience via an internship, work experience, coding competitions, or widely used contributions in open source repositories (e.g., GitHub)
- Proven track record of achieving significant results as demonstrated by grants, fellowships, patents, as well as publications at leading workshops, journals, or conferences such as CVPR, CoRL, ICRA, RSS, NeurIPS, ECCV, ICCV, IROS, or similar