Mapping Analyst - Contract (6 months)

Responsibilities
Map Health Monitoring Monitor map quality and drift indicators across the fleet. Identify stores where localization failures, delocalization events, or navigation errors point to a degraded or outdated map. Remote SLAM Map Generation Remotely control robots in-store using proprietary tooling to drive fresh SLAM mapping traversals when a store's map needs to be rebuilt from scratch. Map Patching from Historical Scans Pull lidar scans from previous traversals and use them to patch, extend, or correct sections of an existing map without requiring a full remap, minimizing on-site disruption. Manual Map Editing Use photo/image editing software to clean up, align, and splice map segments — correcting artifacts, merging patched regions seamlessly, and removing transient obstacles or scan noise that automated processing didn't catch. Quality Assurance Validate patched and newly generated maps against navigation performance before deployment, confirming that fixes resolve the underlying localization issue rather than masking it. Tooling Feedback Work closely with Engineering to flag gaps in the mapping toolchain and inform improvements to automated map-patching and SLAM pipeline tools. Incident Documentation Log mapping-related incidents, root causes, and resolutions in internal tracking systems, and contribute to playbooks for common map failure patterns. Cross-Functional Coordination Partner with Robot Operations, Client Success, and Engineering to prioritize which stores need mapping attention and to communicate expected timelines for fixes.

Qualifications
1–3 years of experience in a technical, spatial-data, robotics, or GIS-adjacent role Comfort with remote robot operation or teleoperation tools, or strong aptitude to learn proprietary robotics tooling quickly Hands-on experience with image/photo editing software (e.g., Photoshop, GIMP, or similar) for precise pixel-level edits Basic understanding of SLAM, lidar data, or occupancy-grid mapping concepts Strong attention to detail — able to spot subtle map artifacts or misalignments that would otherwise cause navigation failures Strong written communication for incident documentation and cross-team coordination Comfort navigating a fast-paced startup environment with evolving tooling and responsibilities

Preferred Qualifications
Prior experience with SLAM algorithms, point cloud data, or robotics navigation stacks Scripting experience (Python or similar) for batch-processing map files or automating repetitive patching tasks Experience with Jira, Confluence, or similar operational tracking tools Retail technology or fleet operations exposure is a plus

Working Conditions
Expected hours: 40 hours per week Working hours: Standard business hours in either west coast or east coast