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AI Wildfire Smoke Plume Tracking Engineer

Aaron Eriksson

Full-time · Job · Los_Angeles

About the role

Air quality agencies currently rely on ground sensors that miss most of a plume's actual footprint. We're looking for an engineer to build models that track smoke density and drift direction from geostationary satellite imagery, updated every ten minutes during fire season. You'll work from raw multispectral tiles through to a public-facing risk layer that public health officials use to issue advisories. Expect to spend real time validating against ground-truth sensor networks, not just chasing benchmark accuracy.

Responsibilities

  • Build plume segmentation models from geostationary satellite tiles
  • Calibrate drift and density estimates against ground sensor networks
  • Ship a near-real-time inference pipeline during fire season
  • Partner with public health teams on advisory thresholds

Requirements

  • Experience with computer vision on satellite or remote sensing imagery
  • Solid tensorflow and numpy fundamentals
  • Comfortable working with gcp-hosted geospatial pipelines
  • Ability to validate model output against noisy ground truth

Benefits

  • Fully remote position
  • Health, dental, and vision insurance
  • Home office stipend
  • Paid time off during off-season

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Categories

AI & Machine Learning Engineers

Skills

python computer vision tensorflow gcp numpy

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Job Type

Full-time

Level

Mid-Level

Language

English

Salary Range

$100k – $130k / year

AI Expertise

AI & Machine Learning Engineers

Skills

python computer vision tensorflow gcp numpy

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