World Labs is a spatial intelligence company, building frontier models that can perceive, generate, and interact with the 3D world. Backed by NEA and a16z.
About the role
We’re looking for a SLAM Specialist to design, implement, and advance state-of-the-art simultaneous localization and mapping systems that enable accurate, robust spatial understanding from real-world sensor data. This role is focused on modern SLAM techniques—both classical and learning-based—with an emphasis on scalable state estimation, sensor fusion, and long-term mapping in complex, dynamic environments.
What they're looking for
- 6+ years of experience working on SLAM, state estimation, robotics perception, or related areas
- Strong foundation in probabilistic estimation, optimization, and geometric vision (e.g., bundle adjustment, factor graphs, Kalman filtering)
- Deep experience with one or more SLAM paradigms (visual, visual-inertial, lidar, multi-sensor, or hybrid systems)
- Proficiency in Python and/or C++, with hands-on experience building research or production-grade SLAM systems
- Experience with numerical optimization libraries and/or robotics frameworks
- Familiarity with learning-based perception or representation learning and how it can augment classical SLAM pipelines
More about this role
World Labs is a frontier AI research and product company advancing spatial intelligence, the next frontier beyond large language models. Co-founded by Dr. Fei-Fei Li , Justin Johnson and Ben Mildenhall , the company is pioneering world models that perceive, generate, reason, and interact with virtual and physical worlds.
The company’s flagship product, Marble , transforms text, images, and video into fully navigable 3D worlds, unlocking applications across gaming, film, architecture, robotics, and immersive digital experiences. Backed by leading investors and with over $1B raised, World Labs is assembling a world-class team at the intersection of AI research and real-world deployment.
We’re looking for a SLAM Specialist to design, implement, and advance state-of-the-art simultaneous localization and mapping systems that enable accurate, robust spatial understanding from real-world sensor data. This role is focused on modern SLAM techniques—both classical and learning-based—with an emphasis on scalable state estimation, sensor fusion, and long-term mapping in complex, dynamic environments.
This is a hands-on, research-driven role for someone who enjoys working at the intersection...
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