---
title: 'Senior Director of Product Management, Models and Data at Niantic Spatial'
canonical: 'https://feeny.ai/job/senior-director-of-product-management-models-and-data-niantic-spatial-london-f2yjdxyb0gc4'
type: 'job'
last_seen: '2026-11-09'
---

# Senior Director of Product Management, Models and Data at Niantic Spatial

- **Company:** Niantic Spatial
- **Location:** London, United Kingdom
- **Employment:** full-time
- **Work type:** hybrid
- **Posted:** 2026-11-05
- **Last confirmed live:** 2026-11-09
- **Apply:** https://jobs.ashbyhq.com/niantic-spatial/39144048-22ac-4574-ba30-6e5862adf893

## 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 can't yet reason about real places well enough for robots, field crews and AI agents to rely on it, and closing that gap will change how factories, power grids, cities and defense operations run. 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

The Large Geospatial Model is Niantic Spatial's foundation model of the physical world. It learns from years of real-world captures of millions of places, and people, robots and AI agents use it to find out where they are, what is around them and what has changed. Each step up in scale has given the model capabilities it did not have before. The next problems are some of the hardest in AI: filling in the parts of a place no camera saw while marking what was inferred, measuring what changed between visits, and predicting what will change next. Customers already use the model in production. Energy companies use it to guide field crews to equipment on large industrial sites, defense partners use it for positioning where GPS is jammed or unavailable, and robotics companies train robots in metric-scale copies of the real sites they will work in. You will be the first product leader for the model and the data it learns from, reporting to the Chief Product Officer. You decide which capabilities it gains and in what order, the bar each release has to clear, and what data Niantic Spatial collects, licenses or partners for to get there. You set those priorities directly with the Chief Scientist and the London research team who train the model. If you have shipped a frontier language model, most of the job will be familiar: evals, data mix and release decisions. The job differs in two ways. Every output of this model can be scored against a measured real place, so its evals rest on ground truth. And its data is collected in the physical world, so choosing what to capture next is a product decision with a real cost. Experience in 3D or mapping is welcome but not required. By the end of your first year, research, engineering and the product leads for industrial, defense, robotics and platform customers work from one model roadmap that you own, each release ships against evals you wrote, and the model's newest capabilities are in customers' hands.

## What You'll Do

- Own the Model Roadmap - Decide the order in which the Large Geospatial Model gains its next capabilities, from filling in unseen parts of a site to measuring and predicting change, based on what industrial, defense, robotics and platform customers will pay for. Turn customer problems into specific research requirements, and bring new research results to the product leads who sell into each market.
- Set the Release Bar - Define the evals and acceptance criteria for each capability with the Real-World Test Lab, which measures model output against ground truth in real places. Decide whether each release ships or goes back for more data or training.
- Own the Data Plan - Decide what data Niantic Spatial collects, buys, licenses or gets through partners, and set the product terms of those deals with Legal and Business Development. Set the curation, labeling, consent, privacy and training-rights requirements every dataset has to meet, and keep a record of which data went into each model version.
- Turn Capabilities into Products - Decide when a new model capability is ready to become something customers buy, what it promises them, and how it reaches them through Niantic Spatial's products and platform.
- Set the Long-Term Direction - Decide where the model goes over the next several years, as it moves from describing places as they are to tracking how they change and anticipating what comes next, and make the case for the research and data investment that takes.

## What You'll Bring

- 8+ years in product management, including at least three years shipping a large model to users or customers.
- Experience writing evals for a model and using them to decide when a release was ready.
- Direct work on training data, such as setting a data mix, running labeling or human-feedback programs, or negotiating data licenses.
- Enough depth in how large models are trained, post-trained and evaluated that researchers bring you into their technical decisions. Many strong candidates for this role were ML engineers or researchers before they moved into product.
- Experience setting direction for research and engineering teams that did not report to you.
- A bachelor's degree in computer science, engineering, or a related field, or equivalent experience.

## Nice to Have

- Experience in 3D computer vision, reconstruction, localization, mapping, geospatial data, robotics or autonomous systems.
- An advanced degree in machine learning, computer vision, robotics, or a related field.
- Experience with Gaussian splatting, neural fields or visual positioning systems.
- Experience with government or defense requirements for data provenance and security.

## 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)

## Other roles at Niantic Spatial

- [Engineering Manager, Device Platforms](https://feeny.ai/job/engineering-manager-device-platforms-niantic-spatial-san-francisco-17q1s40ecgyh) — San Francisco, CA
- [Software Engineer, Infrastructure](https://feeny.ai/job/software-engineer-infrastructure-niantic-spatial-san-francisco-m57tjhm211kn) — San Francisco, CA
- [3D Computer Vision Research Engineer, Geospatial Visual Localization](https://feeny.ai/job/3d-computer-vision-research-engineer-geospatial-visual-localization-niantic-1ff9cc2q6npq) — London, United Kingdom
- [Staff/Senior Staff Computer Vision Engineer - Map team](https://feeny.ai/job/staff-senior-staff-computer-vision-engineer-map-team-niantic-spatial-san-gqk1m7pa51ps) — San Francisco, CA
- [3D Computer Vision Research Engineer - World Map](https://feeny.ai/job/3d-computer-vision-research-engineer-world-map-niantic-spatial-london-80v4ka40p8zy) — London, United Kingdom
- [3D Reconstruction Research Scientist](https://feeny.ai/job/3d-reconstruction-research-scientist-niantic-spatial-london-jtj724025ekz) — London, United Kingdom
- [AI Engineer, Computer Vision](https://feeny.ai/job/ai-engineer-computer-vision-niantic-spatial-san-francisco-z0gjw688cfax) — San Francisco, CA
- [Staff Engineer - Robot Learning, Embodied AI](https://feeny.ai/job/staff-engineer-robot-learning-embodied-ai-niantic-spatial-san-francisco-4ef37kb9rjer) — San Francisco, CA
- [Senior/Staff Product Engineer, Embodied AI](https://feeny.ai/job/senior-staff-product-engineer-embodied-ai-niantic-spatial-san-francisco-76wfnqgtf15f) — San Francisco, CA
- [Hardware Operations Engineer - Robotics, Real-World Test Lab](https://feeny.ai/job/hardware-operations-engineer-robotics-real-world-test-lab-niantic-spatial-san-wda3z89zfvn3) — San Francisco, CA