Data Engineer

Build AI for the future of fruit farming

At Aurea Imaging, we build AI solutions that help fruit growers worldwide make better decisions.

With our TreeScout technology, we collect and process detailed data directly in orchards. TreeScout combines sensing, edge computing and AI, with significant processing already happening on the device.

Over the years, we have built a unique dataset of structured geospatial and agronomic data across countries, climates, seasons and growing conditions. This gives us the opportunity to discover patterns and build predictive models that were previously not possible.

We are looking for a GeoAI Engineer who enjoys combining data science with software engineering and wants to turn unique real-world data into impactful products.

What you'll do

• Develop GeoAI models for applications in fruit farming.
• Discover patterns and insights from the TreeScout data, combined with other data sources to uncover new agronomic insights.
• Build predictive models that support better decisions for growers.
• Turn proof-of-concepts into scalable, production-ready solutions.
• Build and improve data pipelines and AI workflows.
• Improve the performance, reliability and scalability of our AI solutions.
• Translate model outputs into product improvements.

Our technology stack

You will work with:

• Python-based services (including FastAPI).
• Database platforms, including MongoDB and Postgresql.
• Kubernetes-based cloud infrastructure and scalable data processing workflows.
• Big data technologies, including Apache Iceberg.
• Edge devices, including technologies such as Kairos and Nvidia Jetpack.
• MLOps with ClearML, FiftyOne, and CVAT.

Experience with these technologies is a plus. Strong engineering fundamentals and the ability to learn quickly are more important.

Your role

• Become an important contributor to Aurea's GeoAI and Data Science capabilities.
• Help unlock the value of our unique TreeScout dataset.
• Work from early experiments and prototypes through to production systems.
• Collaborate with the team to build reliable products.
• Contribute beyond your core expertise when needed—whether that is improving a backend service, optimising a pipeline or help our field engineers debugging in the orchard.

At Aurea, everyone takes ownership of the end result. We are a small team where your ideas have direct impact.

Who you are

• 3–5 years of experience in data science, machine learning, software engineering or a related field.
• A background in Data Science, Artificial Intelligence, Computer Science, Geoinformatics or similar.
• Strong Python programming skills.
• Experience developing machine learning solutions and bringing them into production.
• Experience working with data-heavy environments, cloud infrastructure, edge computing or IoT is a plus.
• Experience with geospatial data, GIS, remote sensing, or sensor-based data is a plus.
• Curious, analytical, and comfortable solving problems without predefined answers.
• Someone who takes ownership and enjoys working in a startup environment.
• Interested in applying AI and geospatial data to agriculture and sustainable food production.

Working at Aurea

• You will work from our Utrecht office at least three days per week. We believe in the value of working together, sharing ideas and building strong team connections.
• You will join an international team with colleagues from different backgrounds and countries. Aurea has 10 different nationalities!
• Candidates must already have the right to work in the Netherlands. Visa sponsorship is not available for this position.

Why Aurea Imaging?

• Work with a unique global dataset built over multiple years.
• Develop AI solutions that directly impact fruit growers worldwide.
• Work at the intersection of AI, geospatial data, edge computing, and agriculture.
• Have freedom to explore new ideas while building products that create real customer value.
• Join a growing international team in Utrecht with short communication lines and a strong ownership culture.

Excited about using AI and unique real-world data to transform the future of agriculture? We'd love to hear from you.