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AI Driver Fatigue Risk Monitoring Engineer

Miles Andersen

Full-time · Job · Chicago

About the role

The models you'll ship will be used by fleets running 50,000 trips a week across long-haul routes. Fatigue-related incidents cost our customers more than any other single risk category, and cabin cameras generate more footage than any human review team could ever process. You'll build and maintain the models that detect microsleep, eye-closure patterns, and head-nod events in real time on edge hardware installed in the cab, then route confirmed alerts to dispatch within seconds.

Responsibilities

  • Maintain edge-deployed fatigue detection models running in-cab
  • Reduce false alert rates flagged by fleet safety managers
  • Optimize inference for constrained onboard hardware
  • Coordinate with dispatch systems on alert routing and escalation

Requirements

  • Strong computer vision background, ideally with driver monitoring or similar
  • Experience deploying pytorch models to edge or embedded hardware
  • Comfortable with kubernetes-managed fleet update pipelines
  • On-site presence required at our Chicago safety operations center

Benefits

  • On-site role with dedicated hardware lab access
  • Health, dental, and vision insurance
  • 401k matching
  • Relocation assistance

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Categories

AI & Machine Learning Engineers

Skills

python computer vision pytorch kubernetes aws

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