Senior Machine Learning Engineer
AxonSeattle, Washington, United StatesPosted 6 April 2026
Job Description
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
Are you eager to contribute to building AI products impacting the world for the greater good? As an ML Engineer at Axon, you will contribute to developing AI solutions transforming the public safety space and supporting our company’s mission: accelerate justice, protect truth, and save lives. Working closely with other ML engineers and scientists, you will enable new AI capabilities for Axon’s products (Fleet, Draft One, Axon Air, VR and more) by supporting the training, evaluation, testing and deployment of machine learning models on Axon devices and cloud.
As part of a multidisciplinary team, you will be exposed to a wide range of AI domains and applications: from computer vision to speech recognition and natural language understanding.
What You’ll Do
Location: Hybrid from our office in Seattle, Washington.
Reports to: Manager, Machine Learning Engineering
Collaborate with scientists and product managers to build proof-of-concepts (POCs) contributing to shaping the Axon of tomorrow.
Architect and develop secure, privacy-preserving, solutions to enable the continuous improvement of existing AI models.
Architect platforms that accelerate research and AI product development.
Collaborate with scientists in architecting and implementing state-of-the-art training techniques.
Set high standards for ethical and responsible AI development.
What You Bring
Bachelor’s Degree in Computer Science, Engineering, Electronics, Mathematics or an equivalent highly technical field.
6+ years of software engineering experience and a proven track record of successfully deploying AI models to the cloud.
Experience with Infrastructure-as-code and cloud architecture.
Proficiency in Python and C++, familiarity with ML frameworks such as TensorFlow, or PyTorch.
Advanced knowledge and hands-on experience with Linux.
Excellent problem solving skills and ability to dive deep into system architecture.
Excellent software design skills.
Comfort communicating and interacting with scientists, engineers and product managers.
What You Bring
Master’s Degree/PhD in Computer Science, Engineering, Electronics, Mathematics or an equivalent highly technical field.
Experience with LLMOps - evaluation, monitoring, quantization, teacher-learner, etc.).
Hands-on experience with fine-tuning large parameter models.
Familiarity with model encryption and privacy preserving AI techniques.
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
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 a ... (truncated, view full listing at source)
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