Sr Machine Learning Engineer I at Axon

Axon

Seattle, Washington, United States·14h ago

SeniorFull-timePythonAWSMachine LearningTensorFlowPyTorchCI/CDML

Salary Range

$132,600 - $179,400 /year

Estimated

This salary is estimated based on similar roles. The actual salary may vary.

About the Role

We are looking for an Applied Machine Learning Scientist/Engineer focused on Sensor Fusion & Tracking to join Axon. This role involves researching, designing, and validating advanced estimation and probabilistic models for 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.

Key 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.

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.