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AI Carbon Sequestration Modeling Engineer

Violet Adeyemi

Full-time · Job · New_York

About the role

Voluntary carbon markets depend on accurate sequestration estimates — but the current methods are 15 years old and based on sparse field measurements. Satellite imagery, LiDAR data, and soil sensors now make it possible to estimate carbon stocks at 10-meter resolution across entire forest landscapes. We're building the ML pipeline that turns remote sensing data into auditable sequestration estimates that carbon registries will accept. You'll develop regression models that fuse multispectral satellite imagery, elevation data, and historical climate records to estimate above-ground biomass and soil carbon stocks. The scientific challenge: uncertainty quantification that's honest about confidence intervals, because carbon credit buyers and registries need to understand the uncertainty in every estimate they purchase. You'll collaborate with two environmental scientists who understand the ecology and a remote sensing specialist who handles the geospatial data pipeline. No climate science background required, but intellectual curiosity about the domain is essential.

Responsibilities

  • Build ML models estimating carbon stocks from satellite and LiDAR data
  • Develop uncertainty quantification methods for carbon stock estimates
  • Integrate climate and soil data to improve model accuracy
  • Validate model outputs against field measurement ground truth datasets
  • Build pipelines that process large-scale geospatial rasters efficiently
  • Document methodology in formats suitable for carbon registry audits

Requirements

  • 3+ years in ML engineering with geospatial or environmental data experience
  • Experience with regression modeling and uncertainty quantification
  • Python proficiency and comfort with large raster dataset processing
  • Familiarity with remote sensing concepts or geospatial data formats
  • Strong statistical grounding for working with scientific datasets

Benefits

  • Fully remote
  • Mission-aligned company with genuine climate impact
  • 30 days PTO
  • Health and dental coverage
  • $3,500 annual learning and conference budget

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Categories

data science & analytics AI & Machine Learning Engineers

Skills

python pytorch statistics pandas aws

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Job Type

Full-time

Level

Mid-Level

Language

English

Salary Range

$100k – $130k / year

AI Expertise

data science & analytics AI & Machine Learning Engineers

Skills

python pytorch statistics pandas aws spark

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