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Director Machine Learning Jobs in Seattle, WA (NOW HIRING)

Axon

Principal Machine Learning Engineer

Seattle, WA · Hybrid

... new machine learning models and AI capabilities, leading to better and more responsible AI ... Director of Artificial Intelligence * Architect and develop secure, privacy-preserving, on device ...

Axon

Principal Machine Learning Engineer

Seattle, WA · On-site

... new machine learning models and AI capabilities, leading to better and more responsible AI ... Director of Artificial Intelligence * Architect and develop secure, privacy-preserving, on device ...

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Director Machine Learning information

See Seattle, WA salary details

$41K

$104.6K

$160.5K

How much do director machine learning jobs pay per year?

As of Aug 12, 2026, the average yearly pay for director machine learning in Seattle, WA is $104,622.00, according to ZipRecruiter salary data. Most workers in this role earn between $81,400.00 and $120,600.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive in the director machine learning position, and why are they important?

To thrive as a Director Machine Learning, you need advanced expertise in machine learning, statistics, data science, and leadership, typically supported by a master's or Ph.D. in a related field and several years of relevant industry experience. Familiarity with tools such as Python, TensorFlow or PyTorch, cloud platforms, and data management systems, as well as certifications like AWS Certified Machine Learning or Google Professional Machine Learning Engineer, are commonly required. Exceptional communication, strategic thinking, and team management skills distinguish top candidates in this role. These capabilities are essential for driving organizational AI initiatives, fostering high-performing teams, and delivering impactful business solutions.

What is a director machine learning?

A Director of Machine Learning leads teams in developing and deploying machine learning models to solve business challenges. They define the AI strategy, oversee research, and ensure models are scalable and ethical. This role requires expertise in machine learning, data science, and leadership, as well as collaboration with cross-functional teams. Directors also stay updated on industry advancements and drive innovation within their organizations.

What are the primary responsibilities and challenges faced by a director machine learning on a daily basis?

A Director of Machine Learning is typically responsible for overseeing the development and deployment of machine learning solutions, mentoring technical teams, setting strategic direction for AI initiatives, and ensuring the alignment of projects with organizational goals. Challenges often include balancing innovative research with business priorities, navigating evolving technology landscapes, and coordinating efforts across data science, engineering, and stakeholder teams. This role requires regular collaboration with product managers, executives, and cross-functional departments to prioritize initiatives and communicate complex technical concepts. Successful directors excel at fostering a culture of continuous learning, optimizing team productivity, and staying ahead in a fast-paced, rapidly changing field.

What are the most commonly searched types of Machine Learning jobs in Seattle, WA? The most popular types of Machine Learning jobs in Seattle, WA are:
What are popular job titles related to Director Machine Learning jobs in Seattle, WA? For Director Machine Learning jobs in Seattle, WA, the most frequently searched job titles are:
What job categories do people searching Director Machine Learning jobs in Seattle, WA look for? The top searched job categories for Director Machine Learning jobs in Seattle, WA are:
Director Machine Learning jobs near you
Infographic showing various Director Machine Learning job openings in Seattle, WA as of August 2026, with employment types broken down into 1% As Needed, 74% Full Time, 21% Part Time, 1% Temporary, and 3% Contract. Highlights an 89% Physical, 2% Hybrid, and 9% Remote job distribution, with an average salary of $104,622 per year, or $50.3 per hour.

Principal Machine Learning Engineer

Axon

Seattle, WA • Hybrid

Full-time

Medical, Dental, Vision, Retirement, PTO

Re-posted 3 days ago

Axon rating

8.8

Company rating: 8.8 out of 10

Based on 15 frontline employees who took The Breakroom Quiz

14th of 157 rated electronics manufacturers

Job description

Your Impact

Are you passionate about AI? Do you love engineering solutions enabling fast, cutting-edge science? Are you eager to contribute to building products impacting the world for the greater good?
As a Principal ML Engineer at Dedrone, you will contribute to architecting and implementing the platform used by Dedrone scientists to bring safe, secure, reliable AI features to the field of counter UAS devices. Collaborating closely with scientists and software engineers, you will enable new AI capabilities for Dedrone products. As part of a multidisciplinary team, you will be exposed to a wide range of domains and applications: from Multi-modal Sensor Fusion to Real Time Systems with distributed edge compute.
The ideal candidate will have a consistent track record of successfully optimizing models for the edge and deploying AI models at the edge, including on device with limited memory & connectivity, to serve users world wide. They will understand the AI lifecycle and be capable of supporting scientists end-to-end along the development of new machine learning models and AI capabilities, leading to better and more responsible AI solutions. They are willing to be bold and stand up to support the team in enabling drone safety measures across Public Safety, Enterprise and Defense domains.

What You'll Do

Location: Hybrid from Seattle, WA
Reports to: Director of Artificial Intelligence 

  • Architect and develop secure, privacy-preserving, on device solutions to enable the continuous improvement of existing AI models.
  • Collaborate with scientists in architecting and implementing state-of-the-art edge distributed training techniques.
  • Implement on device monitoring solutions used for continuous model improvement
  • Implement innovative model compression solutions to enable AI at the edge.
  • Impact the team by bringing your own expertise and deep knowledge of the state-of-the-art to introduce new techniques leading to tangible impact in terms of model fairness, performance, and platform scalability.
What You Bring
  • Bachelor's Degree in Computer Science, Engineering, Physics, Mathematics or an equivalent highly technical field.
  • 13+ years of software engineering experience and a proven track record of successfully architecting and maintaining large-scale distributed platforms.
  • Experience with AI on chips, on device model deployment and management.
  • Proficiency in python, C++, familiarity with ML frameworks such as TensorFlow, or PyTorch.
  • Advanced knowledge and hands-on experience with on chips development.
  • Excellent problem solving skills and ability to dive into system architecture, design, performance metrics, code, test plans, project plans, deployments and operations
  • Comfort communicating and interacting with scientists, engineers and product managers.
Preferred
  • Master's Degree or PhD in Computer Science, Engineering, Physics, Mathematics or an equivalent highly technical field.
  • Hands-on experience in solving Computer Vision or Natural Language Understanding problems in a business setting.
  • Familiarity with responsible AI, de-biasing, model encryption and de-identification 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
  • 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.

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