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 reasoning skills to help us build a reliable fruit database through consistent data labelling. This role involves manual interpretation of fruit imagery, including estimating fruit edges, colours and quality in partially occluded or challenging lighting conditions. Your precise work will ultimately enable the development of machine learning models.

You will:

• Tag and categorize fruit imagery by applying precise labels and correcting existing annotations to ensure data accuracy.
• Monitor data quality by flagging blurry images, incorrect tags, or inconsistencies in the fruit sets.
• Maintain high annotation accuracy that forms the foundation of our computer vision models

This opportunity is a 6 month contract with the potential for extension based on performance and business needs. Successful candidates will be required to attend a one-week training session at our office in De Waterkant, Cape Town. Thereafter, we encourage in-office attendance on Tuesdays and Thursdays.

What You'll Need

• Higher education degree or diploma
• 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 and able to travel to the office as needed
• Available immediately or as soon as possible

Application Process

• Submit your CV and clear answers to the application questions
• A short take-home assessment will be sent to qualifying applicants.
• Online video interview with the team