About the Role
We're looking for a Perception & Sensor Fusion Engineer to develop the algorithms that give the largest drone swarm in the world an accurate, shared picture of the battlespace. 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 Do
- Train, tune, and test automatic target recognition and track management systems using the latest advancements in neural networks.
- Develop multi-sensor fusion and state estimation algorithms (Kalman filters, particle filters, multi-target tracking) running onboard resource-constrained vehicles.
- 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 Qualifications
- MS 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 experience (training, evaluation, and deployment of neural networks for detection or classification).
- Strong programming skills in C++, Rust, Go, and/or Python.
- Track record of taking algorithms from research to deployment on a real system.
Preferred Qualifications
- Publications or deployed work in ATR, multi-sensor fusion, or distributed estimation.
- Experience with EO/IR, radar, or RF sensor processing on aerial platforms.
- Experience deploying ML models to embedded or edge hardware (TensorRT, ONNX, quantization).
- Familiarity with defense sensing and tracking problem domains.