Introduction

Hey! We’re Delicious Data

We build AI that helps bakeries and food businesses plan perfectly, so they waste less, earn more, and serve with pride.

You’ll join a small, focused engineering team in Munich that values clear thinking, craftsmanship, and real-world impact. Our developers come from diverse backgrounds, from research and data science to large-scale production systems, and share a simple principle: build things that work beautifully.

As a working student, you’ll develop and ship features end to end, learn from experienced engineers, and see your work make a visible difference.

Tasks

• Real forecasting at real scale: Work with time series data from thousands of stores, thousands of products, and years of history totalling over 1 billion records.
• Proprietary ML systems, not off-the-shelf magic: Help develop, improve, and extend our in-house forecasting pipeline that blends deep learning, random forests, and domain knowledge.
• From research to production: You’ll help bring models into production, monitor their performance, analyze failure modes, and iterate based on real customer behavior.
• Food waste, quantified: Your work directly reduces overproduction and saves tons of food every day, with measurable impact beyond the hype.
• Learn by doing, together: Exchange code reviews with senior ML engineers, discuss modeling decisions, and learn how production ML actually works in a fast-moving startup.

Requirements

• You are enrolled in CS or a related program at a university in Bavaria
• You are available 20 hours per week and can work with us onsite in Munich
• You have practical experience with timeseries data and forecasting problems
• Tools like Pandas, scikit-learn, Pytorch are second nature to you
• You are passionate about your work and love to collaborate with others
• You enjoy writing clean, maintainable code and care about performance and usability
• You can communicate clearly in English (C1 level)

Benefits

• Work closely with experienced engineers who care about design, scalability, and quality
• Apply state of the art ML research
• Learn how to build production ready ML models
• A great office at the Sendlinger Tor
• Awesome team events, good coffee, and a culture that prizes clean code, feedback, and collaboration
• Strong long-term perspective: Many of our full-time team members started as working students

Ready to build Delicious Data with us? We’re excited to hear from you.