Sr Machine Learning Engineer I
Core
Research, design, and validate advanced estimation and probabilistic models for real-time airspace awareness systems using multi-sensor fusion and multi-target tracking.
Role type
Senior Applied Machine Learning Engineer (Sensor Fusion & Tracking)
Builds
Real-time airspace awareness systems for drone detection and safety
Domain
Defense & Public Safety / Signal Processing & Estimation Theory
Deliverable
production ML models
Required skills
Multi-sensor fusion, multi-target tracking, probabilistic modeling, state estimation, Kalman filters (EKF/UKF), particle filters, Bayesian filters, probabilistic data association, multi-hypothesis tracking, Python, PyTorch/TensorFlow, MLOps, CI/CD for ML, model versioning, monitoring, automated retraining, large noisy multi-modal datasets
Preferred skills
None explicitly stated
Technologies
Python, PyTorch, TensorFlow
Responsibilities
Research and develop advanced multi-sensor fusion and multi-target tracking methodologies; Design probabilistic models and state estimation frameworks for radar, RF, optical, and other sensing modalities; Develop and evaluate algorithms such as Kalman filters, particle filters, and Bayesian filters; Conduct simulation studies and performance benchmarking across varying operational conditions; Analyze real-world datasets to validate model assumptions and improve robustness; Partner with software engineers to transition validated algorithms into scalable, production-ready systems; Publish internal technical documentation and contribute to intellectual property development
Seniority
Senior, hands-on IC
