Mapping Operations Lead

Applied Intuition Applied Intuition · Robotics · Sunnyvale, CA · Autonomy Tooling Software Engineering

Lead a team responsible for the day-to-day operations of mapping for autonomous vehicles, focusing on data collection, map production, validation, simulation, and field operations. This role involves managing production schedules, triaging issues, and coordinating between mapping specialists, software engineering, and field operations to ensure high-quality HD map data that directly impacts AV stack performance.

What you'd actually do

  1. Lead a team of mapping specialists, setting priorities, managing workloads, and maintaining a clear production schedule across concurrent map build and update cycles
  2. Own the weekly and sprint-level production calendar — balancing incoming requests for mapping new areas, improving map quality, and supporting field tests
  3. Run daily standups and triage sessions; escalate blockers quickly and make real-time prioritization decisions based on operational impact to keep the pipeline moving
  4. Mentor specialists, conduct technical reviews of their work, and establish standards for map labeling, QC, acceptance criteria, and documentation
  5. Serve as the primary escalation point for map data issues flagged during map production, validation, or by downstream consumers, including initial triage, creating actionable followup tasks, and routing to maps and engineering teams for resolution

Skills

Required

  • HD map production
  • geospatial data operations
  • autonomous vehicles
  • robotics
  • mobility
  • leading or coordinating a team
  • HD map data formats (OpenDRIVE, NDS, proprietary lane-level map schemas)
  • annotation pipelines
  • point cloud data
  • 3D visualization environments
  • lidar-based annotation tools
  • simulation environments (CARLA, LGSVL, internal sim stacks)
  • analyzing field reports or sensor data
  • data tooling (SQL, C++, Python, QGIS)
  • written and verbal communication
  • organization
  • calm under pressure

Nice to have

  • LiDAR point clouds
  • camera-based feature extraction
  • standard definition (SD) street network data
  • AV safety operations
  • working alongside safety drivers
  • JIRA
  • Slack
  • defining or improving QA/QC standards in a mapping team
  • working across time zones
  • AI skills

What the JD emphasized

  • 3+ years of experience in HD map production, geospatial data operations, or a closely related field in autonomous vehicles, robotics, or mobility
  • Demonstrated experience leading or coordinating a team of technical contributors
  • Strong understanding of HD map data formats (e.g., OpenDRIVE, NDS, or proprietary lane-level map schemas) and annotation pipelines to label map elements
  • Experience working with point cloud data, 3D visualization environments, or lidar-based annotation tools
  • Familiarity with simulation environments (e.g., CARLA, LGSVL, or internal sim stacks) and how map data feeds into sim validation
  • Experience analyzing field reports or sensor data to identify map quality issues
  • Comfort with data tooling — SQL, C++, Python, QGIS, or similar — for pulling reports, querying map data, and building dashboards