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Salary
$230k – $255k per year
Location
Remote/Hybrid (San Francisco, United States)
Seniority
Senior
Employment
Full-Time

Confirmed on the employer's own hiring board on Sep 24, 2026. First seen by Alion on Sep 23, 2026.

Overview
Company
Impact
Profile match
Niantic Spatial is the geospatial software company formed when Niantic sold its games business to Scopely and kept the mapping technology. It builds a large geospatial model and visual positioning system from the imagery collected by location-based games. Customers use it to anchor augmented reality and robotics to real places.

About Niantic Spatial

At Niantic Spatial, we're building the future of physical AI. Powered by a proprietary database of over 30 billion posed images, our groundbreaking mapping technology unlocks a new dimension of interaction and spatial intelligence that helps both humans and machines better understand, represent, navigate, and engage with the real environment.

Our reconstruction technology captures environments with geometric accuracy and extreme detail from any standard camera, and our Visual Positioning System delivers precise positioning almost anywhere in the world. We serve customers across robotics, the public sector, and energy and industrial markets - building for the 80% of economic activity that takes place beyond our screens.

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 Computer Vision Engineer to join our Embodied AI team. You'll work across research, engineering, product, and customer teams to turn advances in 3D reconstruction and spatial perception into reliable capabilities that embodied AI teams can use in production.

You've taken a prototype and made it work in the real world. You understand that the difficult part is often not the core method, but the messy inputs, edge cases, operational constraints, and downstream requirements surrounding it. You care about quality, cost, latency, and reliability, and you know that a system is only successful when people can depend on it. This is a hands-on engineering role for someone who wants to build, ship, and own outcomes. You'll help shape both the technology and the product, while remaining close to the code and the problems our customers are trying to solve.

What You'll Do

  • Productionize Computer-Vision and 3D Reconstruction Capabilities - Turn research ideas and prototypes into reliable pipeline components and services that can operate across varied customer data and environments.

  • Own End-to-End Output Quality - Ensure that reconstructed environments and spatial artifacts are geometrically coherent, correctly scaled and aligned, and usable by downstream simulation and embodied AI systems.

  • Make Systems Robust to the Real World - Diagnose failures caused by capture quality, scene complexity, scale, calibration, coordinate conventions, and other assumptions that prototypes often leave implicit.

  • Improve Performance, Throughput, and Cost - Profile and optimize GPU and distributed workloads, reduce unnecessary reruns, and help establish the economics of running reconstruction at scale.

  • Build Evaluation and Quality Infrastructure - Create datasets, regression tests, quality gates, and benchmarking tools that help the team measure whether changes improve the system.

  • Shape the Next Generation of Capabilities - Bring production and customer constraints into research planning, helping prioritize the advances that matter most for embodied AI.

  • Work Across the Product Boundary - Partner with Embodied AI product and engineering teams to understand customer requirements and deliver capabilities that fit real training, evaluation, and deployment workflows.

  • Define the Interfaces to Embodied AI Workflows - Help evolve the representations, tooling, and operational systems that allow reconstructed environments to move reliably into customer applications.

What You'll Bring

  • Significant experience building and operating production computer-vision, machine-learning, graphics, or data-processing systems.

  • Hands-on experience with 3D reconstruction, photogrammetry, structure from motion, SLAM, mapping, scene understanding, computer graphics, or a related field.

  • Experience delivering reliable computer-vision or 3D systems used by other teams or customers.

  • Practical command of 3D and spatial data, including geometry, camera models, coordinate frames, calibration, and metric scale.

  • Strong Python skills, with the ability to work in C++ or other performance-oriented environments when needed.

  • Experience with cloud infrastructure, GPU workloads, distributed processing, or large-scale data pipelines.

  • A bachelor's degree in a relevant field, or equivalent experience.

Nice to Have

  • Experience with Gaussian splatting, neural rendering, meshing, or related reconstruction methods.

  • Built evaluation or benchmarking infrastructure for perception or reconstruction systems.

  • Experience with robotics, simulation, or embodied AI applications.

  • Experience optimizing large-scale GPU workloads for cost, throughput, or latency.

Competencies

  • Painful sense of urgency. You make decisions and ship as if the company’s success depends on it, because it does. A-players love working with you and everyone else struggles to keep up.

  • 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 do not let your colleagues sleepwalk into failure.

  • Pragmatic. You have no patience for NIH Syndrome and analysis paralysis. You find the fastest path to a working capability without one-way doors that undermine scaling.

  • Strong systems instincts. You understand that production quality includes reliability, observability, cost, latency, maintainability, and usability-not just algorithmic accuracy.

  • Comfort with ambiguity. You can make progress when the problem, data, and requirements are still evolving.

Compensation & Benefits

Base salary range of $229,500 to $255,000 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.

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