Africa Climate Careers Network's Climate Job Board

Discover emerging career opportunities in the climate and clean energy sectors

Machine Learning Model Builder - Contract

Aerobotics

Aerobotics

Software Engineering, Data Science
Cape Town, South Africa
Posted on Aug 27, 2025

About Aerobotics

Our mission is to provide intelligent tools to feed the world. We do this by delivering actionable tree and fruit insights to growers across 18 countries, powered by imagery and advanced computer vision.

To date, we've analyzed over 340 million trees and 65 million fruit, helping farmers make critical operational and agricultural decisions that maximize yield and efficiency. Our global team of 50+ professionals is headquartered in Cape Town, with commercial offices in the USA, Australia, Portugal, Spain, and South America.

The Opportunity

We're seeking detail-oriented individuals with strong visual and spatial reasoning skills to help build and refine our fruit datasets. This role involves complex visual interpretation of fruit imagery, including estimating fruit edges, colours and quality in partially occluded or challenging lighting conditions.

You will:

  • Complete specialized training in fruit image annotation and quality assessment
  • Review and improve ML datasets by correcting annotations on fruit imagery
  • Identify and report data quality issues and potential process improvements
  • Produce/Maintain high annotation accuracy that forms the foundation of our computer vision models

This opportunity is a 3-month contractor agreement with the potential to extend the contract. Candidates are expected to work in a hybrid setup (Mon, Wed, Fri in office, with Tues & Thurs optional in-office or remote.

What You'll Need

  • Higher education degree or diploma
  • Strong visual and spatial reasoning abilities
  • Excel, Google Sheets and Docs proficiency
  • Excellent attention to detail and analytical thinking
  • Your own laptop and a stable internet connection
  • Based in Cape Town

Application Process

  • A short take-home assessment will be sent to qualifying applicants.
  • Applicants who are successful in the assessment stage will progress to a 15-minute introductory interview.