3D Computer Vision Research Engineer, Geospatial Visual Localization

The role

You will develop Geospatial Visual Localization technologies to help people and robots localize themselves. You will design and evaluate novel visual localization algorithms and train large models on multi-modal datasets.

What you will do

• Design, implement, and evaluate novel visual localization algorithms, combining 3D vision and deep learning.
• Train large models on multi-modal data at scale, and build the benchmarks that measure their accuracy and robustness.
• Develop robust solutions for difficult real-world conditions: noisy or denied GPS, changing appearance, varying capture quality, large geographic extents, and imperfect reference maps.
• Work side-by-side with researchers, engineering, and product teams to turn research into end-to-end solutions.
• Communicate results through technical writing, design reviews, internal presentations, and publications.

Required qualifications

• Strong grounding in 3D computer vision, deep learning, robotics, photogrammetry, or a closely related field.
• Demonstrated experience with multi-view geometry and related problems, such as camera pose estimation, monocular depth estimation, SfM, SLAM, georeferencing, point-cloud registration, or sensor fusion
• Knowledge of transformer models for 3D vision, such as vision foundation models, feed-forward 3D reconstruction, or multi-view and multi-modal attention.
• Knowledge of geospatial data and coordinate reference systems.
• Ability to formulate ambiguous real-world problems, choose appropriate mathematical or learning-based tools, and evaluate solutions rigorously.
• Strong Python skills and experience training deep learning models at scale, with libraries such as PyTorch, NumPy, and SciPy.
• Strong software engineering skills, with the ability to turn research prototypes into reliable, scalable, and maintainable systems.
• Experience taking an algorithm from research idea and experimental prototype through evaluation, benchmarking, and deployment on real-world data.
• Clear written and verbal communication and the ability to collaborate across research and engineering disciplines.

Nice to have

• A PhD in computer vision, robotics, machine learning, photogrammetry, geodesy, remote sensing, or a related field, or equivalent research or industry experience.
• A strong publication record or substantial active involvement in the research community, especially at venues such as CVPR, ICCV, ECCV, NeurIPS, ICLR, SIGGRAPH, SIGGRAPH Asia, 3DV, ICRA, RSS, or relat
• Experience with aerial or satellite imagery, GNSS/GPS, IMUs, LiDAR data, geodesy, mapping systems, or large-scale spatial data.
• Evidence of technical leadership, mentorship, or successful cross-functional delivery.

Benefits

• Annual bonus
• Equity
• Comprehensive benefits package

About the company

Niantic Spatial builds spatial AI models and services so people and machines can reason, learn and act safely in the physical world. They turn camera imagery, video, sensor data and archives into accurate, AI-readable representations of real places.