Sr Machine Learning Engineer I

Axon•Seattle, WA

4d•Hybrid

About The Position

Join Axon and be a Force for Good. At Axon, we’re on a mission to Protect Life. We’re explorers, pursuing society’s most critical safety and justice issues with our ecosystem of devices and cloud software. Like our products, we work better together. We connect with candor and care, seeking out diverse perspectives from our customers, communities and each other. Life at Axon is fast-paced, challenging and meaningful. Here, you’ll take ownership and drive real change. Constantly grow as you work hard for a mission that matters at a company where you matter. Your Impact As an Applied Machine Learning Scientist/Engineer 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.

Requirements

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.

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 (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.