Senior Machine Learning Engineer Seattle, Washington, Seattle, Washington

Location:

Seattle, Washington, United States

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.

• 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.

• Location:
  
  Hybrid from our office in Seattle, Washington.
• Reports to:
  
  Manager, Machine Learning Engineering.

• 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 Tensor Flow or PyTorch.
• Advanced knowledge and hands‑on experience with Linux.
• Excellent problem‑solving skills and ability to dive deep into system architecture.
• Comfort communicating and interacting with scientists, engineers and product managers.

• 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.

• Competitive salary and 401k with employer match.
• Discretionary paid time off.
• Paid parental leave for all.
• Fitness programs.
• Emotional & mental wellness support.
• 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.

The Pay:
Axon is a total compensation company, meaning compensation is made up of base pay, bonus, and stock awards. The starting base pay for this role is between USD 150,750 in the lowest geographic market and USD 221,000 in the highest geographic market. 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

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.

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.

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