Niantic Spatial
First, our founders brought digital mapping to the world. Next, we invented global-scale AR. Now we're building the real-world foundation model for people, AI and robots. We're building for the 80% of economic activity that takes place beyond our screens: robots that lose GPS and drift off course, defense teams with no shared 3D picture of where they operate, facilities where downtime costs millions. Unlike LLMs, which understand language, we build computer-vision models that understand physical space. And unlike generated environments, our models are geometrically accurate and have real-world coordinates - which is what makes physical AI precise and trustworthy. We work across three capabilities for our customers: reconstructing physical spaces as AI-native digital twins using cheap, off-the-shelf cameras; locating and orienting – “localizing” – machines and people within those spaces; and enabling AI to understand and answer questions about the real world.
Open Positions at Niantic Spatial
5 open positions
Join Niantic Spatial as a Computer Vision Research Engineer to innovate in 3D reconstruction technology and spatial AI.
Lead enterprise solution architecture from customer discovery through implementation, integrating spatial intelligence products into cloud, edge, device, and robotics environments. You’ll partner with Sales, Product, Engineering, and delivery teams, with a focus on Energy and Industrial customers.
Lead technical solutioning for federal customers, shaping architectures and proposals from early discovery through operational deployment. You’ll bridge customer missions, business development, product, engineering, security, and delivery across cloud, hybrid, tactical edge, and classified environments.
Build and scale the computer vision systems behind Niantic Spatial’s centimeter-level Visual Positioning System and 3D maps. You’ll turn advanced geospatial algorithms into high-performance production software while providing technical leadership across the mapping stack.
Lead the development of high-performance computer vision systems for 3D reconstruction, localization, semantic mapping, and Gaussian Splatting. This role combines applied research, production C++ and Python engineering, GPU optimization, and technical leadership for a team building geospatial AI capabilities.