Anduril Industries
Computer Vision Engineer
About this role
Anduril Industries seeks a Computer Vision Engineer to develop advanced perception systems for autonomous aerial platforms. You'll design and implement 3D vision algorithms, SLAM systems, and perception integration for complex robotic systems operating in dynamic environments.
What you'll do
- Develop robust 3D perception and computer vision algorithms for real-time autonomous decision-making
- Create structure from motion and SLAM algorithms for accurate 3D modeling from multiple camera inputs
- Integrate perception outputs with path planning for autonomous navigation in unstructured environments
- Design experiments and curate training/evaluation datasets for algorithm development
- Collaborate with robotics, software, and hardware teams on system integration
- Work with vendors and government stakeholders on perception and world modeling advancement
What they're looking for
- 3D computer vision (multi-view geometry, photogrammetry, 3D reconstruction)
- C++ or Rust programming (4+ years)
- Computer vision libraries (OpenCV, PyTorch, NumPy)
- SLAM and structure from motion algorithms
- Robotics and autonomous systems knowledge
- Data structures, algorithms, and code optimization
- Sensor integration (LiDAR, RGB-D, stereo cameras)
- GPU/CUDA programming (preferred)
Opens the application — the Jobs AI extension fills it for you. Set up autofill
Opens the official application on the employer’s site. No login required.
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
- Walk us through your experience developing SLAM or structure-from-motion algorithms. What were the key challenges you faced in making them work in real-time on resource-constrained platforms?
- Describe a time when you had to integrate computer vision outputs with another system (like path planning or controls). How did you handle the latency and accuracy requirements?