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Hadrian

Machine Learning Engineer - Vision

Los Angeles, CAFrom $160kfulltimemidAdded today

About this role

Hadrian seeks a Senior Machine Learning Engineer to own the ML lifecycle for computer vision models powering our manufacturing intelligence platform. You'll develop detection and segmentation systems that analyze manufacturing data—drawings, CAD files, and documentation—to automate Design for Manufacturing processes and drive massive efficiency gains across our autonomous factories.

What you'll do

  • Research, develop, and deploy object detection and segmentation models for document understanding and semantic part analysis
  • Build and maintain annotation tooling, implement active learning loops, and engineer synthetic data augmentation strategies
  • Design evaluation frameworks that measure real-world system impact beyond standard metrics like mAP and IoU
  • Collaborate with the ML team to set technical and product roadmaps for the AI platform
  • Own production deployment and model health monitoring end-to-end
  • Iteratively improve model accuracy to deliver measurable time savings at manufacturing scale

What they're looking for

  • Computer vision (object detection, segmentation)
  • Transformer-based architectures (ViT, Swin)
  • Python and PyTorch (custom training loops, loss functions, data loaders)
  • Production ML deployment and monitoring
  • Data annotation and active learning
  • Synthetic data generation
  • Evaluation framework design
  • Manufacturing domain knowledge (preferred)

Benefits

  • Competitive salary ($160,000–$250,000)
  • Full-time position at a well-funded, rapidly scaling startup
  • Opportunity to impact aerospace and defense manufacturing at scale
  • Collaborative environment with high ownership and autonomy
  • Access to cutting-edge manufacturing facilities and real-world data
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Hadrian

Hadrian builds aerospace and defense manufacturing systems, offering enterprise software platforms, advanced tooling design, and highly automated production capabilities for the sector. The company is hiring full stack engineers, manufacturing and tooling specialists, infrastructure and identity management experts, and workforce systems architects to support its rapid scaling.

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Likely interview questions

  • Walk us through a detection or segmentation model you shipped to production—what were the biggest challenges and how did you measure success beyond standard metrics?
  • Tell us about a time you had to improve model accuracy in the long tail; how did you approach the problem and what techniques did you use?
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