---
title: 'Staff Engineer - Robot Learning, Embodied AI at Niantic Spatial'
canonical: 'https://feeny.ai/job/staff-engineer-robot-learning-embodied-ai-niantic-spatial-san-francisco-4ef37kb9rjer'
type: 'job'
last_seen: '2026-10-19'
---

# Staff Engineer - Robot Learning, Embodied AI at Niantic Spatial

- **Company:** Niantic Spatial
- **Location:** San Francisco, CA
- **Compensation:** $270k–$300k
- **Employment:** full-time
- **Work type:** hybrid
- **Posted:** 2026-10-02
- **Last confirmed live:** 2026-10-19
- **Apply:** https://jobs.ashbyhq.com/niantic-spatial/46d5ab8c-054c-44bd-94ef-f3b65d78d1b4

## 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

Niantic Spatial makes the physical world computable, helping people and machines collaborate safely by aligning how they understand reality. One of the fundamental problems we're helping autonomy teams and engineers overcome is the sim-to-real gap for visual-spatial understanding. We're applying our team's decades of experience encoding the world precisely as it is at Google Maps, Google Earth, and Niantic Labs to build the scalable real-to-sim stack for embodied AI. We're looking for a Staff Engineer, Robot Learning to lead engineering for our real-to-sim product within the Embodied AI group. One of the fundamental problems facing autonomy teams is the sim-to-real gap in visual-spatial understanding, and we're applying decades of experience encoding the world precisely as it is to build the scalable real-to-sim stack for embodied AI. Working alongside the group's General Manager and Product leader, you'll inform the roadmap, own the technical requirements our researchers and engineers build against, and personally prototype and evaluate the changes you propose. You've lived the problems our customers are solving: you've trained and deployed embodied AI systems, seen where and why simulation fails to predict real-world performance, and worked through the consequences. This is not a role for someone who wants to manage and not ship, or someone who wants to ship without ownership of commercial consequences. This is a role for an entrepreneurial tech lead who loves to build and is energized by helping those around them do the best work of their lives. You have a co-founder mentality. You may have been part of a founding team before, or want to start your own business one day.

## What You'll Do

- Sharpen the Roadmap - Bring first-hand knowledge of customer pain, existing solutions, and the value of doing better to roadmap decisions, and help focus effort on the most consequential problems to solve.
- Own the Technical Requirements - Guide the team to design the real-to-sim stack pragmatically. Make the final recommendation on what to build, integrate, and simplify, ensuring capabilities work within customers' existing training and evaluation workflows.
- Benchmark the Impact - Working with our Real-World Test Lab, design and run reproducible evaluations that measure the impact of our real-to-sim stack on policy transfer and real-world performance against customers' existing approaches.
- Build and Ship - Lead engineering delivery and personally build critical features. Keep scope tight, remove blockers, and get performant capabilities into customers' hands quickly.
- Raise the Technical Bar - Set a high bar for the team's work and deepen its understanding of robotics development and deployment, driving incremental improvement every week.

## What You'll Bring

- Experience training, evaluating, and deploying robot policies in systems used by enterprise or government customers, with responsibility for performance in real operating conditions.
- Deep practical experience using simulation for policy training or evaluation, including tools such as NVIDIA Isaac Sim, Isaac Lab, MuJoCo, or equivalent. You have diagnosed sim-to-real failures and understand when greater fidelity improves outcomes.
- Hands-on experience with reinforcement learning, imitation learning, or both, and with deep-learning frameworks such as PyTorch.
- A practical understanding of how visual perception and 3D scene representations affect robotics training, evaluation, and real-world performance.
- Experience running experiments on real robots, from an ambiguous hypothesis through to defensible results.
- Strong Python and C++ skills, with experience building reliable production software.
- A bachelor's degree or higher in a relevant field.

## Nice to Have

- You've authored or maintained a public robotics benchmark.
- You've helped take an early product to repeatable adoption across multiple customers.
- You've built or substantially extended robotics simulation infrastructure, including scene authoring, domain randomization, or large-scale training and evaluation.
- You've trained and deployed vision-based navigation or mobility policies, particularly in varied, unstructured environments.
- You've built pipelines that turn real-world reconstructions into simulation-ready environments.

Competencies

- Always Learning. Staying on top of the latest academic breakthroughs and commercial advancements, particularly in real-to-sim-to-real.
- Relentless bias for action. You make decisions and ship as if the company’s success depends on it, because it does. You set the pace, and drive the people around you to rise to it.
- Intellectually honest. You know there’s just one job that underpins every other in a startup: find the truth. You are relentless in your pursuit of it, including when it challenges your own convictions, and you raise concerns when you see them — even when it's uncomfortable, and especially when it's unpopular.
- Pragmatic. You have no patience for not-invented-here syndrome and analysis paralysis. You find the fastest path to delivering customer value without going through one-way doors that undermine future scaling.
- Confident and credible with customers. You can sit alongside an autonomy engineer and help them get to the root of their problems. You are comfortable speaking to customers and bring commercial nous to those discussions.

## Compensation & Benefits

The expected salary range for this role is $270,000 – $300,000 per year. Compensation also includes an annual bonus, equity, and a comprehensive benefits package including medical, dental, and vision coverage, 401(k), and more.

Location & Work Model This role is based in our San Francisco 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

- [3D Reconstruction Research Scientist/Engineer](https://feeny.ai/job/3d-reconstruction-research-scientist-engineer-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
- [Software Engineering Intern (Summer 2027)](https://feeny.ai/job/software-engineering-intern-summer-2027-niantic-spatial-san-francisco-hqycgn6h604f) — San Francisco, CA
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- [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
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- [Research Scientist, Embodied AI](https://feeny.ai/job/research-scientist-embodied-ai-niantic-spatial-london-6pmyhj4kvh95) — London, United Kingdom
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