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Location
In office (Atlanta)
Employment
Full-Time
Overview
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AeroVect is an autonomous driving technology company headquartered in San Francisco, California, and founded in 2020. The company develops the AeroVect Driver, an AI-powered software platform designed to automate ground support equipment such as baggage tractors and cargo haulers at airports. Its solutions are deployed at major passenger and cargo hubs globally to improve operational safety, reduce labor costs, and enhance reliability in airside environments.

Who We Are

AeroVect is transforming ground handling with autonomy, redefining how airlines and ground service providers around the globe run day-to-day operations. We are a Series A company backed by top-tier venture capital investors in aviation and autonomous driving. Our customers include some of the world’s largest airlines and ground handling providers. For more information, visit www.aerovect.com.

Job Description

We are looking for a Mapping Engineer to own the creation and validation of the high-definition maps that our autonomous tractors drive on. AeroVect builds category-defining autonomy for airport airside operations, and every deployment depends on accurate, safe, production-grade maps of structured, low-speed environments - taxiways, aircraft stands, and indoor baggage halls.

This is a hands-on, end-to-end ownership role based on-site in Atlanta. You'll be the single point of contact for incoming mapping requests, build and update maps through our map repository and Map CI pipeline, and validate map changes in simulation and on the tractor here in Atlanta before it ships. You'll work closely with autonomy, operations, and test engineers, and report into the mapping/autonomy team.

This is an excellent entry point for someone early in their career who is detail-obsessed, wants to work close to real hardware, and is excited to own a process from request to deployment. We'll train you on our tools - what matters most is rigor, reliability, and a strong sense of ownership.

You Will:

  • Own the mapping request queue end to end: intake requests, clarify requirements with the requester, scope the work, and communicate status through to completion.

  • Create and edit HD maps (lanes, intersections, routes, regulatory elements, goal poses) using JOSM and our in-house lanelet tooling on the Lanelet2 / OpenStreetMap data model.

  • Submit map changes as pull requests through the map repository, following our "maps as code" workflow and getting them green through Map CI (validation, connectivity, and path-feasibility checks).

  • Validate every change in simulation first, then test on the tractor in Atlanta as needed.

  • Capture evidence (sim videos, test results, before/after diffs) and document testing results

  • Maintain map hygiene - pruning duplicates, keeping naming and versioning consistent, and documenting the process so it scales beyond one person.

  • Coordinate with external mapping vendors to validate and integrate large-scale map deliveries.

You Have:

  • A Bachelor's degree (completed or in progress) in Computer Science, Geomatics/GIS, Robotics, Engineering, or a related field - or equivalent practical experience.

  • Strong attention to detail and a methodical, safety-minded approach to repetitive, high-stakes work.

  • Comfort with Git and a standard pull-request / code-review workflow.

  • Basic scripting ability (Python preferred) and comfort working on Linux and the command line.

  • A strong sense of ownership, clear written communication, and the ability to keep a request queue organized under shifting priorities.

  • Based in or willing to relocate to Atlanta, and comfortable working on-site with the vehicle.

We Prefer:

  • Experience with mapping or GIS tools (JOSM, QGIS, OpenStreetMap) or HD map formats (Lanelet2, OpenDRIVE).

  • Exposure to ROS / ROS2 and autonomy stacks

  • Familiarity with CI/CD pipelines, AWS S3, or simulation tools such as CARLA.

  • Geospatial fundamentals: coordinate frames, aerial imagery alignment, point clouds.

  • Experience working in a fast-moving startup environment.

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