Principal ML Engineer - Edge AI & On-Device Deployment

SHPE Houston; Seattle, Northern (WA, KY); Hybrid; USD 177,000 - 283,000; Full time

Benefits offered by this job

Competitive salary

401k with employer match

Discretionary PTO

Medical, Dental, Vision

Learning & Development

ERGs

Snacks in office

Job summary

Axon is seeking a Principal ML Engineer to architect and implement on-device AI solutions for edge deployment, collaborating with scientists and engineers to enable new capabilities across our platforms. You will drive end-to-end development from model design to deployment in constrained environments worldwide.

The ideal candidate has a proven track record of optimizing edge models, deploying on-device AI, and leading cross-functional initiatives in safety-related domains.

Qualifications

• Bachelor's degree in CS, engineering, physics, mathematics or related technical field.
• 13+ years of software engineering with distributed platforms.
• Experience with AI on chips and on-device model deployment/management.
• Proficiency in Python and C++, with ML frameworks such as TensorFlow or PyTorch.

Responsibilities

• Architect and develop secure, privacy-preserving on-device AI solutions for edge deployment.
• Collaborate with scientists to implement state-of-the-art edge distributed training techniques.
• Implement on-device monitoring for continuous model improvement.
• Develop model compression techniques to enable AI at the edge.
• Contribute expertise to improve model fairness, performance, and platform scalability.

Skills

Python

C++

On-device deployment

Edge AI

System architecture

Problem solving

Communication

Education

Bachelor's Degree in Computer Science or related field

Master's Degree or PhD preferred

Tools

TensorFlow

PyTorch

ML frameworks

Job description

Axon is seeking a Principal ML Engineer to architect and implement on-device AI solutions for edge deployment, collaborating with scientists and engineers to enable new capabilities across our platforms. You will drive end-to-end development from model design to deployment in constrained environments worldwide.

The ideal candidate has a proven track record of optimizing edge models, deploying on-device AI, and leading cross-functional initiatives in safety-related domains.