--- title: 'Senior/Staff Product Engineer, Embodied AI at Niantic Spatial' canonical: 'https://feeny.ai/job/senior-staff-product-engineer-embodied-ai-niantic-spatial-san-francisco-76wfnqgtf15f' type: 'job' last_seen: '2026-10-19' --- # Senior/Staff Product Engineer, Embodied AI at Niantic Spatial - **Company:** Niantic Spatial - **Location:** San Francisco, CA - **Compensation:** $207k–$265k - **Employment:** full-time - **Work type:** hybrid - **Posted:** 2026-09-30 - **Last confirmed live:** 2026-10-19 - **Apply:** https://jobs.ashbyhq.com/niantic-spatial/a09075f5-ae36-4b3c-ae4c-d33e2e17a60b ## 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 Senior/Staff Product Engineer to join our Embodied AI team. Working alongside the group's GM, Product leader, and robot learning engineer, you'll own how the product reaches customers, build the integrations that make it native to their simulators and deployment stacks, and influence the roadmap. You've turned capabilities into products. You've shipped developer-facing products and watched adoption turn on details nobody planned for. You know that a capability isn't a product until someone outside the building has used it without help, and you're passionate about the work that sits between the two. 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 engineer who loves to build and is energized by making the people around them, researchers and customers alike, more effective. 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 - Build the Product Surface - Own how autonomy teams experience our work: the APIs, UIs, packages, and documentation. - Make Our World Native to the Customer's - Turn scans and reconstructions into reliable, interoperable assets that work in customers' simulation tools and workflows, including packaging, metadata, semantic labels, object structure, and selectable variants. - Turn Prototypes Into Capability - Partner with reconstruction, mapping, localization, and research teams to transform prototypes and pipeline outputs into production-grade services and user experiences. - Deliver at Scale - Design and operate backend systems for accounts, organizations, sites, scans, assets, processing jobs, permissions, asynchronous workflows, storage, and data access. - Make It Work - Work directly with customers and internal users to integrate our technology, diagnose failures, improve reliability, and close the gap between intended and actual product behavior. - Influence the Roadmap - Work alongside the group's GM, Product leader, and robot learning engineer to shape what we build and when. ## What You'll Bring - 6+ years of software engineering experience; Bachelor's degree in Computer Science or a related field, or equivalent practical experience. - Significant experience building and operating production web applications and backend services, with strong fundamentals in API design, data modeling, testing, observability, and reliability. - Shipped developer-facing products — including the documentation and reference code external engineers actually used — and worked with 3D asset formats or comparable binary formats to production depth: you can say what the conventions were, where they broke, and what it cost you. - Proficient in Python and TypeScript, comfortable working across frontend and backend, and able to take a feature from product requirements through to running it in production. - Experience designing asynchronous workflows, long-running jobs, external integrations, and data-intensive systems. ## Nice to Have - Experience working with robotics simulators or toolchains such as Isaac Sim, Isaac Lab, or MuJoCo, or OpenUSD. - Built products for geospatial, 3D, computer vision, graphics, robotics, or spatial computing. - Worked on visualization or asset-management experiences with React, Next.js, or Three.js. Competencies - 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 a working capability without one-way doors that undermine scaling. - Confident and credible with customers. You can read an autonomy engineer's training config, find why our asset didn't load, and explain the fix in their terms. - Fluent in other people's ecosystems. You'll spend much of your time learning new tools and stacks. You're quick to learn the customer's language, and you can point to something you shipped in a world that was foreign to you a quarter earlier. ## Compensation & Benefits The base salary range for this role is $207,000 - $265,000, and your offer within it will reflect your experience and the scope you take on. 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 - [Staff Engineer - Robot Learning, Embodied AI](https://feeny.ai/job/staff-engineer-robot-learning-embodied-ai-niantic-spatial-san-francisco-4ef37kb9rjer) — 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 - [AI Automation Engineer, Real-World Test Lab](https://feeny.ai/job/ai-automation-engineer-real-world-test-lab-niantic-spatial-san-francisco-dv63c1vyxy94) — San Francisco, CA - [Senior Computer Vision Engineer, Embodied AI](https://feeny.ai/job/senior-computer-vision-engineer-embodied-ai-niantic-spatial-san-francisco-b1gqp4bj6mbr) — San Francisco, CA - [Research Scientist, Embodied AI](https://feeny.ai/job/research-scientist-embodied-ai-niantic-spatial-london-6pmyhj4kvh95) — London, United Kingdom - [GTM, Embodied AI](https://feeny.ai/job/gtm-embodied-ai-niantic-spatial-san-francisco-emef5va1xyyt) — San Francisco, CA - [Senior Product Marketing Manager, Embodied AI](https://feeny.ai/job/senior-product-marketing-manager-embodied-ai-niantic-spatial-san-francisco-8bymzx8g9pk9) — San Francisco, CA