Computer Vision Software Engineer, Software Defined Weapon OpticActive$198K

Anduril Industries
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The opportunity

Our Anduril Warfighter Systems division is building the next generation of precision engagement systems. We are developing a software-defined weapon optic that fuses real-time computer vision, sensor data, and onboard processing to dramatically increase first-round accuracy for the warfighter.

What you'll do

  • Designing and developing real-time target detection, classification, and: tracking models and algorithms optimized for low-compute, embedded environments (e.g., Qualcomm-based platforms).

  • Building and refining camera and sensor calibration pipelines (offline and: online) for multi-sensor weapon sight assemblies, including thermal and electro-optical sensors.

  • Developing pose estimation and localization algorithms using techniques such: as bundle adjustment, feature detection/matching, homography fitting, and multi-view geometry.

  • Profiling, optimizing, and deploying vision models and algorithms on: constrained hardware — managing trade-offs between accuracy, latency, and power consumption.

  • Creating testing and evaluation frameworks: designing experiments, analyzing field and production data, and establishing metrics for detection/tracking and overall algorithm performance under operational conditions.

  • Collaborating closely with firmware, mechanical engineering, and: manufacturing teams to integrate vision software into production weapon sight hardware.

What they're looking for

  • MS or PhD in Robotics, Computer Science, Electrical Engineering, Mechanical: Engineering, Mechatronics, or related field.
  • Experience with industrial computer vision systems, counter-UAS applications, or precision targeting systems.
  • Hands-on experience with Qualcomm processors/platforms (e.g., Snapdragon) or similar embedded vision SoCs.
  • Experience with multi-camera and multi-sensor (EO/IR) systems and associated calibration techniques.
  • Proficiency with mathematical/optimization packages in C++ and Python (e.g.,: Ceres, Eigen, OpenCV, NumPy, SciPy).
  • Experience training, optimizing, and deploying detection/tracking models with: TensorRT, SNPE, ONNX Runtime, or similar inference frameworks for edge deployment.
  • Familiarity with real-time operating systems (RTOS) or embedded Linux environments.
  • Familiarity with numeric computing platforms such as MATLAB, Octave, or Jupyter.