Sr Machine Learning Engineer II

Join Axon and be a Force for Good.

As an Senior Machine Learning Engineer II focused on Sensor Fusion & Tracking, you will research, design, and validate advanced estimation and probabilistic models that power Dedrone’s real-time airspace awareness systems. Your work will shape the mathematical foundations behind multi-sensor fusion, multi-target tracking, and uncertainty modeling in complex environments. This role offers the opportunity to translate cutting-edge theory into deployed systems that support critical safety missions worldwide.

Location: Hybrid from Seattle, WA

• 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 (EKF/UKF), particle filters, Bayesian filters, probabilistic data association, and multi-hypothesis tracking.
• Conduct simulation studies and performance benchmarking across varying operational conditions and noise environments.
• Analyze real-world datasets to validate model assumptions, quantify uncertainty, and improve robustness.
• Partner closely with software engineers to transition validated algorithms into scalable, production-ready systems.
• Publish internal technical documentation and contribute to intellectual property development where applicable.
• Stay current with advancements in tracking, estimation theory, probabilistic modeling, and machine learning research.
• Bachelor’s or Master’s degree in Computer Science, Electrical Engineering, Applied Mathematics, or related field — or equivalent hands-on experience building ML systems in production.
• 8+ years of experience developing and deploying machine learning systems in real-world applications.
• Well-developed proficiency in Python and experience with ML frameworks such as PyTorch, TensorFlow, or similar.
• Experience deploying ML systems in production environments (cloud, edge, or embedded systems).
• Solid understanding of statistics, model evaluation, and performance trade-offs.
• Familiarity with MLOps practices including CI/CD for ML, model versioning, monitoring, and automated retraining workflows.
• Experience working with large, noisy, or multi-modal datasets.
• Clear communication skills and a collaborative mindset aligned with Axon’s values: Aim Far, Win Right, Own It, Join Forces, and Be Obsessed with the Customer.

…