Computer Vision/Machine Learning Research Scientist (Spatial AI)

The Reality Labs team at Meta is looking for Computer Vision Researchers to support our Spatial AI team as we build towards our goal to transform the way people come together to interact, work and play.

We explore, develop and deliver cutting-edge technologies that serve as the foundations for the current and future Reality Labs products including VR, AR, smart-glasses, AI agents, and robotics. We are committed to driving the state-of-the-art forward through innovation across ML perception in 2D and 3D, for both primitives (e.g. depth, segmentation, and semantic keypoints) as well as high-level (e.g. shape inference, 3D reconstruction, context/semantic understanding).

The ideal candidate will help us develop the next generation of spatial and contextualized AI, and lay the foundations for a new computing paradigm that is built from the ground up to understand the physical world from egocentric devices. We are looking for experts in areas such as vision-language models, agentic AI, learning from demonstration, and representation learning.

The potential to change the world is immense -- and we're just getting started. We encourage you to apply and join us!Computer Vision/Machine Learning Research Scientist (Spatial AI) Responsibilities

• Design and development of novel machine learning algorithms to solve problems in areas such as: vision-language models, agentic AI for multimodal systems, foundation models, 3D reconstruction with deep learning methods, depth estimation, semantic segmentation, 2D and 3D semantic key point detection, and object tracking
• Define, build, and benchmark new capabilities needed for the next generation of AI
• Communicate cross-functionally
• Drive the team's goals and technical direction to pursue technical opportunities
• Lead and collaborate with multidisciplinary engineering and research teams to develop technologies from early exploration and incubation to production

Minimum Qualifications

• PhD degree in the field of Artificial Intelligence, Robotics, Computer Vision, Machine Learning, Natural Language Understanding, or equivalent practical experience
• Significant industry experience in relevant areas
• Leadership experience driving high-risk, high reward projects scientifically, including managing a team of research scientists and communicating to leadership
• Proven track record of achieving results as demonstrated by grants, fellowships, patents, as well as first-authored publications at conferences such as CVPR, ICCV, NeurIPS, or similar
• Experience handling concurrent projects where timelines may be ambiguous or changing, and prioritizing by balancing required effort with resulting impact
• Experience in Python

Preferred Qualifications

• Experience with distributed systems or on-device algorithm development
• Experience communicating research for public audiences of peers
• Experience working and communicating cross-functionally in a team environment
• Significant industry experience in relevant robotics related research areas, preferably large multimodal models, agentic AI, 3D reconstruction with deep learning methods
• Leadership and interpersonal communication experience in working across many disciplines, driving best practices, and mentorship
• Experience with deep learning frameworks (such as pytorch, tensorflow) and Python
• Experience solving complex problems and comparing alternative solutions, tradeoffs, and different perspectives to determine a path forward

About Meta 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.


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