Principal Machine Learning Engineer

Axon Axon · Enterprise · Office, WA · 2024 Dedrone R&D

This Principal ML Engineer role focuses on architecting and implementing on-device AI solutions for counter UAS systems. The role involves optimizing and deploying AI models at the edge, including on devices with limited memory and connectivity, and supporting the end-to-end AI lifecycle for continuous model improvement and new AI capabilities. It emphasizes collaboration with scientists and software engineers in a multidisciplinary team, working with multi-modal sensor fusion and real-time systems with distributed edge compute.

What you'd actually do

  1. Architect and develop secure, privacy-preserving, on device solutions to enable the continuous improvement of existing AI models.
  2. Collaborate with scientists in architecting and implementing state-of-the-art edge distributed training techniques.
  3. Implement on device monitoring solutions used for continuous model improvement
  4. Implement innovative model compression solutions to enable AI at the edge.
  5. 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.

Skills

Required

  • Python
  • C++
  • TensorFlow or PyTorch
  • on chips development
  • system architecture
  • design
  • performance metrics
  • code
  • test plans
  • project plans
  • deployments
  • operations

Nice to have

  • Master’s Degree or PhD
  • Computer Vision
  • Natural Language Understanding
  • responsible AI
  • de-biasing
  • model encryption
  • de-identification techniques

What the JD emphasized

  • optimizing models for the edge
  • deploying AI models at the edge
  • on device with limited memory & connectivity
  • on device model deployment and management
  • on chips development

Other signals

  • deploying AI models at the edge
  • optimizing models for the edge
  • on device model deployment and management