Anduril Industries
Software Engineer, Robotics Tracking and Fusion
About this role
Join Anduril Industries as a Software Engineer specializing in robotics tracking and sensor fusion for defense applications. You'll design and deploy advanced algorithms for target tracking and state estimation, leading a small team to deliver mission-critical real-time systems that transform military capabilities.
What you'll do
- Design and prototype state-of-the-art tracking and multi-sensor fusion algorithms for real-time deployment
- Lead technical direction of a small team leveraging expertise in target tracking and state estimation
- Develop high-performance software for tactical systems, simulations, and decision support tools
- Build robust filters, estimators, and probabilistic reasoning systems from noisy sensor data
- Validate system performance through high-fidelity simulations and statistical analysis
- Integrate tracking technologies into broader software lifecycle and customize for mission-critical use cases
What they're looking for
- C/C++ and Python programming
- Kalman filters, particle filters, and multi-target tracking algorithms (JPDA, MHT, PHD)
- Bayesian filtering and sensor fusion techniques
- Signal processing for radar, lidar, and EO/IR sensors
- Applied mathematics (linear algebra, optimization, probability, stochastic processes)
- Machine learning for target tracking and classification
- Big data pipelines and NoSQL databases
- Estimation theory and adaptive filtering
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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 implementing Kalman filters or particle filters for target tracking applications—what challenges did you encounter and how did you overcome them?
- How have you applied Bayesian filtering techniques to multi-sensor fusion problems, and what sensor types have you worked with?