S Robotics develops autonomous retail robots that generate thousands of scenes per store to enhance the retail experience. The Mapping Quality Lead role focuses on ensuring the quality of store maps created by these robots before they are delivered to clients. This position is part of a team managing an increasing volume of store maps and aims to establish a robust, repeatable Quality Assurance pipeline. The pipeline will be critical for onboarding new retail customers, and the role involves hands-on process ownership, system refinement, and continuous improvement to support scalable, high-quality mapping operations.
Postula directamente desde Get on Board.
Design & maintain the Audit Sheet – build formulas, data-validation rules, conditional formats, QC tab, and lightweight Apps Script automations.
Own the metrics stack – create daily / weekly dashboards that track throughput, error types, root-cause trends, and on-time performance; flag insights to Mapping Ops and auditing leadership.
Continuously refine the checklist – capture new edge cases, update visual examples, and publish one-page quick-reference guides.
Health-check the process – spot-sample ≈ 10 % of audits each day to verify adherence; escalate systemic issues (not individual errors) to the auditing team lead.
Close the feedback loop with Mapping Ops – log defects (e.g., delocalization, waypoint gaps), track fixes to completion, and re-validate maps before client release.
Package the playbook – consolidate SOPs, Loom walkthroughs, and copy-paste templates so future teams can spin up the pipeline with minimal lift.
Process-driven QA mindset – you turn recurring defects into preventive checks and clear documentation.
Advanced Google Sheets – pivot tables, array formulas, data-validation workflows; Apps Script or other automation experience is a plus.
Data-storytelling – ability to translate dashboard insights into concise, actionable updates for technical and non-technical stakeholders.
Visual diagnosis – comfortable spotting anomalies in robot captures, map overlays, or other scene imagery.
Remote collaboration fluency – clear written English, async updates, and comfort working across US–LATAM–EU time zones.
Exposure to robotics, GIS/mapping, or LiDAR/SLAM data
Familiarity with large-format retail operations (e.g., grocery, warehouse clubs)
Experience building QA pipelines for image- or video-rich data sets
12 weeks, 35-40 hours per week, $15-$20/hr DOE.
GETONBRD Job ID: 54713
Totalmente remoto
El trabajo es 100% remoto desde cualquier país.
Global
Argentina
Chile
Colombia
México
Remoto
Estados Unidos
Superpower AI
.png){kind=logo}
Postula con Google
