Swarm Aero is redefining air power, building the largest swarming UAV and the most versatile swarming aircraft network in the world.
The company is moving quickly to launch the first aircraft designed specifically for swarming, as well as the Command & Control software to mobilize swarms of thousands of heterogeneous autonomous assets and empower human operators to achieve superhuman results.
The team has created and exited multiple startups, negotiated defense deals worth billions of dollars, and designed and built 30+ novel aircraft, with aerospace experience from Scaled Composites, Airbus, Archer Aviation, Blue Origin, and Boom Supersonic.
This is a deep algorithm role for someone who lives in the details of detection, tracking, and estimation, and wants to see their work fly.
What You'll DoTrain, tune, and test automatic target recognition and track management systems using the latest advancements in neural networks.
Design distributed fusion approaches that combine tracks across the swarm into a single coherent picture.
Rigorously characterize algorithm performance against real-world flight data and simulation.
Optimize models and estimators for real-time inference on edge compute.
Write clean, maintainable, and efficient code.
Travel up to 25% of the time for onsite test and integration events.
Basic QualificationsMS or PhD in Robotics, Computer Science, Electrical Engineering, Applied Math, or related field, or equivalent depth of applied experience.
Demonstrated expertise in estimation theory and multi-target tracking (Kalman/particle filters, JPDA, MHT, random finite sets, or similar).
Hands-on deep learning experien.