---
title: '3D Reconstruction Research Scientist at Niantic Spatial'
canonical: 'https://feeny.ai/job/3d-reconstruction-research-scientist-niantic-spatial-london-jtj724025ekz'
type: 'job'
last_seen: '2026-11-02'
---

# 3D Reconstruction Research Scientist at Niantic Spatial

- **Company:** Niantic Spatial
- **Location:** London, United Kingdom
- **Employment:** full-time
- **Work type:** hybrid
- **Posted:** 2026-10-15
- **Last confirmed live:** 2026-11-02
- **Apply:** https://jobs.ashbyhq.com/niantic-spatial/63ea8a24-5d45-4b76-824f-aff4f4b50427

## Job description

## 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

We are looking for 3D Reconstruction Research Scientist to join our Research Team in London. Our team researches and builds the 3D reconstruction technology behind Niantic Spatial's platform. These pipelines turn casually captured or domain specific imagery into high-fidelity explorable 3D reconstructions. This entails anything from Structure-from-Motion through to 3D Gaussian Splatting, feed-forward models, and generative models. Our team shipped 360 splatting to consumers and enterprise customers, developed the splatting tech that runs on phones, shipped multiple POCs to enterprise customers, and have innovated on countless AR technologies. Our team has published at top venues (CVPR, ICCV, ECCV, SIGGRAPH); more often than not, our papers end up in production. We're hiring a researcher to work at both ends of that pipeline. You will implement and iterate on the state-of-the-art for both academic publishing and production, regularly working on prototypes with a short turnaround into customer-facing production. You will work alongside world-class researchers in computer vision, machine learning, graphics, and robotics to develop new approaches for large-scale spatial understanding, localization, reconstruction, scene understanding, and geospatial foundation models.

## What You’ll Do

- Conduct original research in computer vision, machine learning, and spatial AI.
- Design, implement, and evaluate novel algorithms for:
- 3D reconstruction
- Neural scene representations
- 3D Gaussian Splatting
- Geometric deep learning
- Structure-from-Motion (SfM)
- Meshing
- Feed-forward models
- Generative models
- Spatial foundation models
- Collaborate with research scientists and engineers to transition promising ideas into future products.
- Develop large-scale experiments and benchmarking frameworks.
- Work directly with the realities of production with real capture conditions, real hardware constraints, and real customers.
- Publish research findings at leading conferences such as CVPR, ICCV, ECCV, or SIGGRAPH.

## What You’ll Bring

- PhD in Computer Vision, Robotics, Machine Learning, Computer Science, Mathematics, Physics, or a closely related field. Exceptionally strong candidates with equivalent experience in industry would be considered.
- A strong research track record in 3D computer vision: reconstruction, depth estimation, novel view synthesis, SfM, SLAM, or closely related areas.
- Strong publication record at top-tier conferences such as CVPR, ICCV, ECCV, SIGGRAPH, NeurIPS, etc.
- Strong programming skills in Python and experience in PyTorch.
- Evidence that you can carry an idea from research into something real; that may be a shipped feature, a production pipeline, a widely used open-source release, or similar.
- Ability to independently drive research projects from idea generation through experimentation and publication.

## Nice to Have

- Experience with classical reconstruction tooling (COLMAP or similar).
- C++ or CUDA experience, and a feel for performance and on-device constraints.
- Experience with traditional 3D techniques — meshing, texturing, or bringing modern geometry or generative representations into native 3D.

## Compensation & Benefits

Base salary: Competitive market rate. Compensation also includes an annual bonus, equity, and a comprehensive benefits package.

Location & Work Model This role is based in our London office, with three days per week in office.

Inclusive Application We know the strongest candidates don’t always tick every box. If you’re excited about this role and believe you could do it well, we encourage you to apply even if your experience doesn’t match every qualification listed — you may be exactly who we’re looking for.

## Equal Opportunity

Niantic Spatial is an equal opportunity employer. Individuals seeking employment at Niantic Spatial are considered without regard to race, color, ancestry, national origin, religion, creed, age, gender (including pregnancy, childbirth, breastfeeding or related medical conditions), marital status, physical or mental disability, medical condition, genetic information, military or veteran status, gender identity, gender expression, sexual orientation, or any other protected category under applicable laws. Niantic Spatial will also consider qualified applicants with criminal histories in accordance with applicable laws. Please contact your recruiter if you want to request an accommodation for the job application or interview process.

Candidate Privacy I understand that by submitting my job application, the information I provide as part of that application will be used in accordance with Niantic Spatial’s Privacy Notice for Job Applicants and Candidates https://www.nianticspatial.com/applicant-privacy-notice.

## About Niantic Spatial

## Company Overview
- **One-liner**: Niantic Spatial builds real-world foundation models and spatial intelligence systems that enable machines to reconstruct, localize within, and understand the physical world at global scale.
- **Entity Type**: Private (startup, spun out of Niantic in 2025)
- **Headquarters**: San Francisco, CA, USA (with offices in Sunnyvale, Bellevue, London, and Tokyo)
- **Founded**: 2025 (as Niantic Spatial; roots trace back to Keyhole, founded 2001, and Niantic Labs, 2011)
- **Founders**: John Hanke (Founder & Executive Chairman); Thomas Gewecke (CEO), Brian McClendon (CTO), Inhi Cho Suh (President & COO)

## Core Business
- **Primary industry/industries**: Geospatial AI, physical AI infrastructure, spatial computing, robotics, defense, energy, construction, logistics
- **Target customers**: B2B – enterprises in robotics, oil & gas, defense, large venues, construction, logistics; public sector; also powers consumer apps via Scaniverse
- **Mission or purpose statement**: “Build a living model of the world that people and machines can talk to.”

## Products & Services
- **Large Geospatial Model (LGM)** – The core engine trained on one of the largest datasets of real‑world spatial imagery. It powers reconstruction, localization, and understanding capabilities at global scale. Accessed via Scaniverse and licensed to partners. (Model/API)
- **Reconstruct** – High‑fidelity, geo‑referenced 3D models (meshes and Gaussian splats) created from any standard camera, 360° camera, drone, LiDAR, or satellite imagery. (Technology/Service)
- **Localize (Visual Positioning System)** – Precise global positioning and orientation for humans and machines, even in GPS‑degraded or denied environments (indoors, outdoors, anywhere). (Technology/API)
- **Understand** – Spatial foundation models that give AI the ability to reason about the physical world: semantic understanding at every 3D point, queryable in natural language. (Technology/API)

## Market Standing
- **Valuation/Market Cap**: Not disclosed (private company)
- **Key Metric**: Over 300 million user‑contributed scans; 30+ billion posed images from real‑world locations; 140+ patents filed or pending
- **Notable Investors/Partners**: Backed by Niantic (the Pokémon GO creator) and its internal resources; no external funding round publicly announced. Partnerships in defense, energy, construction, logistics, and large venues.
- **Growth Signals**: Formed as an independent company in 2025; actively hiring for senior engineering roles (Computer Vision, Tech Lead, AI Data Operations); expanding from consumer AR into enterprise and government sectors.

## Competitive Advantages
- **Deep heritage**: Founders built Keyhole (acquired by Google, became Google Earth/Maps) and later created the world’s first global Visual Positioning System at Niantic.
- **Unique data moat**: 300M+ crowdsourced scans and 30B+ posed images provide a proprietary dataset of real‑world spatial imagery that competitors would find extremely difficult to replicate.
- **Planetary‑scale deployment**: Proven ability to operate at global scale (Pokémon GO had 500M+ users); technology already battle‑tested in demanding consumer and enterprise environments.
- **Patent portfolio**: 140+ patents covering spatial reconstruction, localization, and understanding.

## Strategic Focus
- Continue building spatial foundation models that can reason about the physical world in natural language
- Expand vertical markets: robotics (warehouse, delivery, autonomous), defense (DDIL environments), oil & gas (facility digital twins), large venues, and construction
- Drive adoption of the Large Geospatial Model (LGM) as the standard for physical AI reasoning
- Integrate consumer‑facing Scaniverse as the front door to the LGM, simultaneously feeding the model with new user scans

## Why Work Here
- **Culture & mission**: High‑impact startup environment focused on a mission to create a living 3D model of the world; employees describe it as fast‑moving and collaborative
- **Work model**: Hybrid – blends in‑office collaboration with flexibility. Offices in San Francisco, Sunnyvale, Bellevue, London, and Tokyo.
- **Benefits**: 100% paid healthcare for employees, short‑/long‑term disability & life insurance (premiums covered), generous parental leave, flexible time off, 401(k) with company match, stock option grants (equity participation), and legal assistance (ARAG).
- **Engineering culture**: Deep technical challenges in computer vision, geospatial AI, large‑scale ML, and robotics; tight‑knit team of experts from Google Earth, Niantic, and the AR industry.
- **Growth trajectory**: Newly independent company with strong backing, ample opportunity to shape the product and technical direction.

## Sources
1. [nianticspatial.com – Homepage](https://www.nianticspatial.com/)
2. [nianticspatial.com – Careers](https://www.nianticspatial.com/careers)
3. [nianticspatial.com – About](https://www.nianticspatial.com/about)
4. [nianticspatial.com – About (alternate)](https://www.nianticspatial.com/en/about)

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