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.
What You'll Do 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.
What You Bring- 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.
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
Axon is a total compensation company, meaning compensation is made up of base pay, bonus, and stock awards. The actual base pay is dependent upon many factors, such as: level, function, training, transferable skills, work experience, business needs, geographic market, and often a combination of all these factors. Our benefits offer an array of options to help support you physically, financially and emotionally through the big milestones and in your everyday life. To see more details on our benefits offerings please visit https://www.axon.com/careers.
Base Pay Range
$150,750-$241,200 USD
Don't meet every single requirement? That's ok. At Axon, we Aim Far. We think big with a long-term view because we want to reinvent the world to be a safer, better place. We are also committed to building diverse teams that reflect the communities we serve.
Studies have shown that women and people of color are less likely to apply to jobs unless they check every box in the job description. If you're excited about this role and our mission to Protect Life but your experience doesn't align perfectly with every qualification listed here, we encourage you to apply anyways. You may be just the right candidate for this or other roles.
Important NotesThe above job description is not intended as, nor should it be construed as, exhaustive of all duties, responsibilities, skills, efforts, or working conditions associated with this job. The job description may change or be supplemented at any time in accordance with business needs and conditions.
Some roles may also require legal eligibility to work in a firearms environment.
