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3D Reconstruction Research Scientist/Engineer

🏢 Niantic Spatial · 📍 London · 💼 hybrid · ⏰ FullTime
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Position Summary & Responsibilities

About Niantic Spatial

AI has learned from almost everything online, but it still struggles with the physical world, where 99.5% of economic activity happens. It doesn’t know where things are, how spaces fit together, or what changes over time.

That’s one of the biggest unsolved problems in AI, and it’s the one we’re solving at Niantic Spatial. We build spatial AI models and services so people and machines can reason, learn and act safely in the physical world. We turn camera imagery, video, sensor data and archives into accurate, AI-readable representations of real places that robots can train in and machines can use to know exactly where they are.

In physical AI, mistakes have real consequences. That’s why we build AI grounded in measured reality, not guesswork, so the people and machines relying on it can trust it to get things right.

Our team built some of the world’s most widely used maps. Now we’re building something bigger: a living, measured record of the real world that machines can query, learn from and use to understand how places change over time. If you want to help AI understand the world we actually live in, come build with us.

About the Role

You’ll join our Research Team in London as a 3D Reconstruction Research Scientist/Engineer — working at both ends of the pipeline, from cutting-edge academic research to shipping directly to customers. Our team builds the reconstruction technology that turns casually captured or domain-specific imagery into high-fidelity 3D reconstructions: everything from Structure-from-Motion through 3D Gaussian Splatting, feed-forward models, and generative models. We’ve shipped 360 splatting to consumers and enterprise customers, developed the splatting tech that runs on phones, and published at CVPR, ICCV, ECCV, and SIGGRAPH — more often than not, our papers end up in production.

You’ll work alongside world-class researchers in computer vision, machine learning, graphics, and robotics on large-scale spatial understanding, localization, reconstruction, scene understanding, and geospatial foundation models. This role is open to junior and senior researchers; scope and responsibility are calibrated to your experience.

🎯 Candidate Preparation Guide For Niantic Spatial Applicants

Key Role Competencies & Evaluation Highlights

Key Role Focus:

Assessing computer vision expertise, 3D spatial mapping, and AR rendering performance constraints.

📋 Preparation Priorities (Key Areas to Clarify):
  • 1. Relying on heavy, unoptimized machine learning models that drain mobile battery instantly
  • 2. Treating 3D coordinate spaces theoretically without practical rendering awareness
  • 3. Failing to account for variable lighting, occlusion, and GPS drift in outdoor AR
✨ Recommended Role Alignment Hook:

I bridge computer vision and spatial computing to build low-latency AR experiences that anchor seamlessly to the physical world.

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