AI Data Operations Manager

At Niantic Spatial, we’re building the future of geospatial AI. Powered by a proprietary database of over 30 billion posed images and a groundbreaking third-generation digital map, our mission is to develop spatial intelligence that helps both humans and machines better understand, navigate, and engage with the physical world. Our high-fidelity mapping technology unlocks a new dimension of interaction—laying the foundation for AI to truly comprehend and operate within real-world environments. Join us as we build a living model of the world that people and machines can talk to. Niantic Spatial’s R&D Operations team powers our AI and mapping capabilities with high-quality real-world data. The AI Data Operations Manager will own end-to-end operations for AI data capture, geo scanning, and labeling programs, working across internal teams and external vendors to deliver reliable, high-quality datasets for research, ML, and product use cases. This role combines hands-on program management of field data collection (360 cameras, RGB LiDAR, drones) with scalable data and labeling operations management. Responsibilities End-to-end AI data operations Own day-to-day operations for geo data, scanning, and labeling programs that power AI models and mapping products. Ensure data workflows run efficiently, on time, and at the right cost/quality bar across internal teams and vendors. Maintain rigorous data tracking and inventory so stakeholders clearly understand what data exists, where it lives, and its readiness and constraints. Field data capture (360, LiDAR, drone) Plan and manage large-scale field capture programs using 360 cameras, RGB LiDAR, and drones, including complex urban mapping operations and targeted customer captures. Coordinate surveyors and vendors to execute capture schedules, resolve in-field issues, and maintain safety and compliance standards. Keep up to date with the latest mapping processes and their impact on scanning requirements; contribute field insights into the evolution of Niantic’s Photon devices and capture tooling. Execute direct, internal data capture when required by specific security protocols, data sensitivity, or when the project scale does not necessitate external vendor mobilization Vendor and partner management Act as the primary operational point of contact for key external partners such as capture vendors and annotation vendors, and for strategic customer programs. Translate customer and internal stakeholder needs into clear scopes of work, SLAs, and procedures for vendors; monitor performance and drive continuous improvement. Labeling and data quality operations Manage labeling operations to provide research, ML, and product teams with high-quality labeled datasets, including defining taxonomies, guidelines, and QA processes. Distill customer requirements into precise labeling instructions and workflows; balance quality, time, and cost tradeoffs and communicate them transparently. Program management, risk, and reporting Lead multi-month, multi-vendor operations such as large-scale drone and 360 capture campaigns (e.g., city-scale mapping projects and DroneToGround dataset expansions). Identify and manage risks, issues, and escalations across all active programs, ensuring stakeholders understand options and tradeoffs. Develop and execute continuous improvement plans for tools, workflows, metrics, and reporting to increase efficiency and reliability over time. Cross-functional collaboration and governance Represent AI data operations in cross-functional forums with Product, Engineering, Research, Legal, Finance, Procurement, Security, and GTM teams. Partner with Legal on data privacy, GDPR/DSA compliance, and data usage governance for customer and internal datasets. Manage budgets and resources for scanning and labeling operations, including forecasting capacity and making resourcing recommendations. Requirements Bachelor's degree in a related field (e.g. Geospatial, Engineering, Operations, Data Science) or equivalent practical experience. 3+ years of experience in operations, data operations, or technical program management, ideally in mapping, geospatial, or AI/ML data domains. Demonstrated experience running real-world data collection and/or labeling operations, including managing outsourced or vendor teams. Hands-on experience with geo data workflow management, field scanning, and visual data labeling; familiarity with GIS or mapping tools is a plus. Strong analytical, problem-solving, and project management skills; able to turn