Anduril Industries
Computer Vision Engineer, Space
About this role
Anduril Industries seeks a Computer Vision Engineer to develop perception systems for autonomous spacecraft across multiple orbital regimes. You'll design and implement computer vision algorithms, integrate hardware sensors with flight software, and validate systems for space domain awareness and rendezvous/docking operations.
What you'll do
- Design and develop computer vision algorithms for spacecraft perception including object detection, tracking, and 3D reconstruction
- Integrate classical and machine learning computer vision methods with hardware sensors and flight software
- Develop test plans and validate CV systems during ground testing, on-orbit commissioning, and operational phases
- Create flight software, firmware, and simulation products for autonomous spacecraft autonomy across LEO, MEO, GEO, and rendezvous missions
- Collaborate with Sensors, GNC, Avionics, Systems, and Mission Operations teams on subsystem integration and testing
- Support spacecraft operations during ground checkout, launch windows, and on-orbit commissioning
What they're looking for
- C++ development in Linux environments
- Computer vision algorithms (object detection, tracking, segmentation, SLAM, visual odometry)
- 3D geometry and multi-view geometry techniques
- Machine learning model development and benchmarking
- Spacecraft GNC, orbital mechanics, and rendezvous proximity operations
- Hardware-in-the-loop simulation and monte-carlo analysis
- Sensor fusion (RGB-D, LIDAR, multi-band sensors)
- Flight software design and validation testing
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Anduril Industries
Anduril Industries builds autonomous defense systems including underwater vehicles, unmanned aircraft, and electronic warfare platforms for the Department of Defense. The company is hiring across mechanical engineering, mission operations, software development, technical leadership, and advanced manufacturing roles to support the design, deployment, and production of these mission-critical systems.
- Website
- anduril.com
Likely interview questions
- Describe your experience developing and benchmarking machine learning algorithms on large-scale datasets, and how you optimized for deployment constraints.
- Walk us through a computer vision project where you integrated both classical geometric methods and neural network approaches—what were the tradeoffs?