Research Scientist - 3D Reconstruction

About the role

SpAItial is building world models that natively understand the physics and geometry of our environment to support industries like robotics, AR/VR, and gaming. We are seeking a Research Scientist to advance methods for recovering accurate camera poses and geometry from real-world imagery. You will work with both classical multi-view geometry and state-of-the-art learned reconstructors to improve robustness and accuracy.

Responsibilities

• Design camera pose estimators and 3D reconstructors.
• Build robust SfM and camera tracking pipelines for a variety of input imaging sensors.
• Develop bundle adjusters and nonlinear optimizers, including non-perspective camera formulations.
• Integrate and extend SOTA feed-forward reconstructors.
• Advance deep multi-view stereo, learned matching, and monocular depth methods for dense geometry.
• Build evaluation metrics for pose accuracy and reconstruction quality, and drive improvements against public & internal benchmarks.
• Scale reconstruction methods to large, diverse real-world datasets while keeping them reliable and efficient.
• Collaborate with researchers to bring reconstruction advances into production systems.

Required skills

• Multi-view geometry
• SfM
• SLAM
• Python
• PyTorch
• Ceres
• COLMAP
• ORB-SLAM

Nice to have

• Production-grade 3D reconstruction

Qualifications

• PhD in computer vision with a research focus on 3D reconstruction
• Publications at top venues (CVPR, ICCV, ECCV, NeurIPS)

About the Company

SpAItial is pioneering the next generation of World Models, pushing the boundaries of generative AI, computer vision, and the simulation of reality. We are moving beyond 2D pixels to build models that natively understand the physics and geometry of our world.