Sr Machine Learning Engineer I

Your Impact

As a Senior Machine Learning Engineer at Dedrone by Axon, you will design, build, and deploy machine learning systems that power real-time detection, classification, tracking, and airspace-awareness capabilities.
You will bridge research and production by transforming promising models into reliable, scalable, and high-performance systems. You will work across the full machine learning lifecycle—from data analysis and experimentation through deployment, monitoring, and continuous improvement—and help deliver critical safety capabilities to customers worldwide.

What You’ll Do

Location: Hybrid from Seattle, WA 

• Design, develop, and deploy machine learning models for real-world sensing and perception applications.
• Build training, evaluation, and inference pipelines that support rapid experimentation and reliable production releases.
• Analyze large, noisy, and multi-modal datasets to identify data-quality issues, improve model performance, and increase robustness.
• Define meaningful offline and online evaluation metrics that connect model performance to customer and product outcomes.
• Optimize models and inference systems for production constraints such as latency, compute, memory, bandwidth, and reliability.
• Deploy and operate machine learning systems across cloud, edge, and embedded environments.
• Monitor production model performance, investigate failures and degradation, and improve models based on field data.
• Develop and improve MLOps capabilities, including model and data versioning, automated testing, CI/CD, deployment, and monitoring.
• Partner closely with scientists, software engineers, and product teams to turn prototypes into scalable, production-ready capabilities.
• Provide technical leadership through architecture reviews, design documentation, code reviews, and mentorship.
• Stay current with advances in machine learning, model optimization, evaluation, and production ML systems.

What You Bring

• Bachelor’s or Master’s degree in Computer Science, Electrical Engineering, Applied Mathematics, or a related field—or equivalent hands-on experience building machine learning systems.
• 8+ years of experience developing and deploying machine learning systems in real-world applications.
• Strong Python proficiency and experience with machine learning frameworks such as PyTorch, TensorFlow, or similar.
• Experience taking machine learning capabilities from experimentation through production deployment and ongoing operation.
• Experience deploying models in cloud, edge, or embedded environments.
• Strong understanding of statistics, experimental design, model evaluation, and performance trade-offs.
• Experience working with large, noisy, imbalanced, or multi-modal datasets.
• Familiarity with MLOps practices such as automated training and evaluation, model versioning, CI/CD, monitoring, and reproducible experimentation.
• Strong software engineering fundamentals, including testing, maintainable design, version control, and production debugging.
• Ability to communicate technical decisions clearly and collaborate across research, engineering, and product teams.
• A collaborative mindset aligned with Axon’s values: Aim Far, Win Right, Own It, Join Forces, and Be Obsessed with the Customer.

Benefits that Benefit You

• Competitive salary and 401k with employer match
• Discretionary paid time off
• Paid parental leave for all
• Medical, Dental, Vision plans
• Fitness Programs
• Emotional & Mental Wellness support
• Learning & Development programs
• Employee Resource Groups (ERGs)
• And yes, we have snacks in our offices

Benefits listed herein may vary depending on the nature of your employment and the location where you work.

Location: This role is based out of our Seattle, WA office and follows a hybrid schedule. We rely on in-person collaboration and ask that team members work onsite Tuesdays through Fridays, with the flexibility to work remotely on Mondays, unless there is an approved workplace accommodation. We believe that connection fuels innovation, and our in-office culture is designed to foster meaningful teamwork, mentorship, and shared success.

#LI-Hybrid