swarmaero - Perception & Fusion Engineer
Requirements
• 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. • 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.
Responsibilities
• 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.
Benefits
• Meaningful equity in a high-growth defense technology company • Competitive base salary commensurate with experience • Medical, dental, vision, and 401k • PTO and paid sick leave • Monthly wellness stipend • Daily catered lunch (office) • Paid parental leave • Direct impact on a critical national security mission • A world-class team of engineers and operators solving genuinely hard problems
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