Posted last month
Staff Software Engineer, Localization
@ AeroVect
Toronto, Ontario
Overview
AeroVect is hiring a Staff Software Engineer for its Localization team to own parts of the localization, mapping and calibration stack for autonomous ground operations at major airports. The role involves owning production reliability on real hardware, building online validation and tooling, and contributing to release gating. Full-time.
Responsibilities:
- Own parts of localization, mapping and calibration stack
- Drive localization to production reliability at airports
- Build online localization integrity validation
- Develop diagnostics and post-mission analysis tooling
- Contribute to regression and release-gating for localization
Requirements summary:
- 8+ years in robotics or autonomous vehicles
- Owned localization or state estimation in production
- Strong modern C++ and Linux with ROS/ROS2
- Non-linear optimization or filtering expertise
- BS or MS in a related field
Tools & skills
Source and dates
Employer career site / ATS feed · ashby
- Employer posting date
- 2026-09-24
- First seen by our source
- 2026-10-08
- Source record updated
- 2026-10-09
These dates describe the source record, not a live verification that the employer is still hiring. Check the original posting.
Job details
| Seniority | Senior |
| Department | Software development |
| Experience | 8+ years |
| Hours per week | 40 (estimated) |
| Work setting | Laboratory, Client sites, Outdoors |
| Position | Sitting and standing |
| Physical demands | physical low · computer high |
| Languages | English |
| Education | Bachelor’s degree (required), Master’s degree (preferred) |
| Fields of study | Computer Science, Robotics, Electrical Engineering, Mechanical Engineering |
Summary and details written by AI from the posting; the employer’s posting is the authority.
AeroVect
Saved company profile
Historical company information from a saved The Jobs API profile (LinkedIn/Crunchbase fields). It is not live-verified; figures may have changed. Missing values remain unknown.
The Airport Automation Company
Full company description
AI-powered airport logistics automation solutions, trusted by the world's largest airlines and airports.
- LinkedIn followers
- 5,376
- People associated on LinkedIn
- 63
- Reported office locations
- 233 E Harris Ave, South San Francisco, California 94080, US
- Toronto, Ontario, CA
- Atlanta, Georgia 30308, US
- Frankfurt, DE
- New York, 10007, US
- Business categories
- Air Transportation
- Robotics
- Software
- Logistics
- Transportation
- Artificial Intelligence (AI)
- Aerospace
- Autonomous Vehicles
- Manufacturing
- Other recorded names
- AeroVect
- Specialties
- Aviation
- Autonomous Driving
- Aerospace
- Transportation
- Logistics
- Airport Automation
- Physical AI
- and Artificial Intelligence
- Profile identifies a recruitment agency
- No
- Reported total investment
- 27,000,000
Currency and observation date were not supplied; this is not a current valuation or a funding round.
AI-powered airport logistics automation solutions, trusted by the world's largest airlines and airports.
| Field | Value |
|---|---|
| Industry | Airlines and Aviation |
| Company size | 51-200 employees |
| Headquarters | South San Francisco, California |
| Organization type | Privately Held |
| Year founded | 2020 |
| Specialties | AviationAutonomous DrivingAerospaceTransportationLogisticsAirport AutomationPhysical AIand Artificial Intelligence |
| Open jobs on Jobsy | 15 |
| View page |
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.
We are looking for a Staff Software Engineer to join the Localization team and own significant parts of our localization, mapping, and calibration stack as we scale autonomous ground operations across major airports. You'll take deep ownership of specific workstreams, contribute to the team's technical direction, and partner across the perception, planning, and platform interfaces to help drive the autonomous system from supervised operation to driverless. You'll work alongside the team's senior localization engineers.
You Will
Take ownership of one or more core areas of the localization stack (LiDAR-inertial-GNSS state estimation, 3D mapping and map maintenance, or sensor calibration) and drive it to production reliability on real hardware at active airports
Contribute across the broader localization and mapping pipeline from sensor integration, performance tuning, regression testing, and deployment to new operating environments
Help design and build online validation that monitors localization integrity and cross-sensor consistency during live missions, detects drift, and integrates with the vehicle's safety architecture
Develop tooling for diagnostics, health logging, and post-mission analysis across the stack
Contribute to the regression, validation, and release-gating approach for localization changes deployed to active airports
Deploy, test, and iterate using data from real autonomous operations
You Have
8+ years in robotics or autonomous vehicles, with a track record of owning localization or state-estimation systems through production deployment on real hardware
Deep practical grounding in multi-sensor fusion and state estimation across LiDAR, IMU, GNSS, and cameras
Demonstrated technical leadership - driving architecture across teams, setting direction, and being the person others escalate to on hard estimation problems
Strong command of non-linear optimization (Ceres, GTSAM, g2o) and/or filtering (EKF, UKF), with the judgment to know when each applies
Strong modern C++ (C++17+) and deep working experience with Linux and ROS/ROS2
Understanding of how calibration quality propagates through localization and perception, and how localization errors propagate into the safety case
BS or MS in Computer Science, Robotics, Electrical/Mechanical Engineering, or a related field
We Prefer
MS or PhD with a focus on localization, state estimation, or calibration
Hands-on experience with multi-sensor calibration - intrinsic, extrinsic, and temporal
Experience with factor graphs, graph-based SLAM, or open-source tools like GLIM, LIO-SAM, Cartographer, Kalibr, Ceres, GTSAM
Experience building online/runtime monitoring and defining safety-relevant thresholds within a safety monitoring architecture
Track record of taking an autonomous system toward driverless operation
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