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Edge AI Developer

Blake Goldberg

Full-time · Job · Los_Angeles

About the role

Our smart agriculture sensors sit in fields across 6 states, running CV models on low-power ARM processors with no internet connection. They detect crop diseases, estimate yield, and identify pest infestations — all in real-time, all at the edge. When a sensor flags an issue, the farmer gets an alert on their phone within seconds. You'll optimize and deploy ML models for edge devices with severe compute constraints. That means model quantization, pruning, architecture search for efficiency, and building the OTA update pipeline that pushes new models to 4,000 devices in the field. The gap between a model that works on a V100 and one that works on a Cortex-A53 is where you live. Our cloud team handles training. Your job starts after the model is trained — making it small enough, fast enough, and reliable enough to run in a cornfield with no cloud fallback.

Responsibilities

  • Optimize ML models for deployment on low-power ARM edge devices
  • Implement quantization and pruning strategies that preserve accuracy
  • Build and maintain the OTA model update pipeline for 4,000 field sensors
  • Design inference benchmarking frameworks for edge hardware
  • Collaborate with the cloud ML team on training-to-edge deployment workflows

Requirements

  • 3+ years in ML engineering with edge or embedded deployment experience
  • Strong PyTorch and TensorFlow Lite skills
  • Experience with model optimization (quantization, pruning, distillation)
  • Familiarity with ARM architectures and embedded Linux
  • Comfort working with hardware constraints and real-world deployment

Benefits

  • Fully remote — US West Coast hours preferred
  • Competitive salary with equity
  • $2,500 learning budget
  • Impact on sustainable agriculture

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Categories

AI & Machine Learning Engineers MLOps & AI Infrastructure

Skills

python pytorch tensorflow docker aws

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Job Type

Full-time

Level

Mid-Level

Language

English

Salary Range

$100k – $130k / year

AI Expertise

AI & Machine Learning Engineers MLOps & AI Infrastructure

Skills

python pytorch tensorflow docker aws

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