Senior Computer Vision Engineer, Embodied AI

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.

Responsibilities

• 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.

Requirements

• Significant experience building and operating production computer-v