Jobs at Niantic Spatial, Inc.

Own the roadmap, evaluation standards, data strategy, release decisions, and long-term direction for Niantic Spatial’s Large Geospatial Model. Translate customer needs into research requirements, define model acceptance criteria using real-world ground truth, oversee data acquisition and governance, and turn new model capabilities into commercial products. Partner with research, engineering, legal, business development, and customer-facing teams across industrial, defense, robotics, and platform markets.

Develop novel 3D computer vision and deep learning algorithms for geospatial visual localization. Train large multimodal models, create robustness benchmarks, and solve localization challenges involving noisy GPS, changing environments, varied sensors, and imperfect maps. Collaborate with research, engineering, and product teams to deploy reliable systems at production scale, communicate findings, and publish research.

Develop algorithms and production systems for world-scale geospatial registration, 3D geometry, correspondence, mapping, and learned 3D reasoning. Build datasets, pipelines, benchmarks, and evaluation methods using imagery, point clouds, LiDAR, GPS, and geographic data. Apply computer vision, machine learning, transformers, and geometric optimization to improve a living world map, while collaborating across research, engineering, and product teams and communicating results through technical documentation and presentations.

Conduct research and develop algorithms for 3D reconstruction, computer vision, spatial AI, neural scene representations, Gaussian splatting, and generative models. Publish at leading conferences, build large-scale experiments, prototype rapidly, and transition research into customer-facing production systems. Collaborate with researchers and engineers across computer vision, machine learning, graphics, robotics, and geospatial modeling. The role requires strong Python and PyTorch skills, a 3D vision research record, top-tier publications, and evidence of shipping research-driven products.

Research Scientist developing embodied AI and spatial intelligence systems, including spatial representations, real-to-sim pipelines, 3D scene understanding, simulation-based learning, and robotic policy evaluation. The role involves creating prototypes, applying generative and diffusion models to 3D data, collaborating across research and product teams, publishing findings, and deploying successful innovations at production scale.