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Shearwater Aerospace

AI-powered autonomous UAV mission planning

Autonomy Software Engineer

Flight Dynamics & GNCConfirmed live in the last 24 hours
Full-timeMontreal, QC, CanadaNo salary listed

About the Job

Requirements

  • Three or more years of experience developing path-planning, trajectory-optimization, or flight-control systems.
  • Strong understanding of UAV flight dynamics and performance modeling.
  • Experience with optimization algorithms.
  • Understanding of atmospheric sciences or integrating weather data into planning systems.
  • Strong proficiency in Python and C/C++ for performance-critical algorithm development.
  • Solid software engineering fundamentals and a commitment to clean, maintainable code.
  • Experience with automated testing and containerization using Docker.
  • Comfort with version control using Git and collaborative development workflows.
  • Willingness to learn Golang quickly and contribute to backend services.
  • Willingness to contribute to frontend work using Vue3/CesiumJS and to cloud deployments when needed.
  • Only candidates with a valid Canadian work visa will be considered.

Responsibilities

  • Design and implement path-planning algorithms that integrate atmospheric data, terrain constraints, and flight-performance characteristics.
  • Develop flight-performance models that account for wind, weather, and aircraft dynamics.
  • Build optimization algorithms for weather-aware route planning and dynamic rerouting.
  • Implement production-grade autonomy software emphasizing reliability and real-time performance.
  • Integrate path-planning systems with frontend visualization using Vue3/CesiumJS and backend services using Golang and REST APIs.
  • Contribute to cloud deployment pipelines and infrastructure on Google Cloud Platform.

Desired Qualifications

  • A degree in Aerospace Engineering, Robotics, Computer Science, or a related field.
  • Background in meteorology, atmospheric science, or weather modeling.
  • Experience with meteorological data formats such as NetCDF and GRIB, and numerical weather prediction models.
  • Knowledge of robotics frameworks such as ROS/ROS2 or flight controllers such as PX4 and Ardupilot.
  • Experience with simulation environments such as Gazebo, jsbSim, or X-Plane.
  • Previous work in the UAV, autonomous-vehicle, or robotics industry.
  • Published research in path planning, motion planning, or trajectory optimization.
  • Familiarity with geospatial libraries such as GDAL, GeoPandas, or PostGIS.
  • Understanding of airspace regulations and aviation standards.

About the Company

Shearwater Aerospace

AI-powered autonomous UAV mission planning

Shearwater Aerospace provides AI-powered autonomy, Smart Flight, to coordinate multiple drones and generate dynamic flight routes for professional and commercial UAVs. Smart Flight analyzes airspace rules, weather, obstacles, and wind, and continuously adapts routes while coordinating fleets to avoid collisions. Compared to competitors, it emphasizes scalable, adaptive, and compliant autonomous flight with wind-energy optimization to extend mission range and reduce costs. The goal is to enable many safe, legal, and economical drone missions at large scale.

Company size
11-50
Company stage
Seed
Total funding
$3M
Headquarters
Montreal, Canada
Founded
2019

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