AI Engineer

Zellerfeld is revolutionising the footwear industry with the world’s first 3D-printing technology for fully customizable shoes. Our goal is simple: printed shoes on every foot. We’re a passionate team of engineers, designers, and innovators, questioning the status quo and disrupting traditional manufacturing processes. Backed by founders, influencers, and celebrities who believe in our vision, we’re committed to making a lasting, positive impact—not just on the footwear industry, but on the world.

Your Mission You'll design, develop, and deploy AI and machine learning solutions that push the boundaries of what's possible in footwear manufacturing. As our AI Engineer, you'll be a key contributor to Zellerfeld's technological advancement — building the models and pipelines that improve our products, enhance maintenance, and solve complex problems no one has tackled before. From data acquisition to model deployment, you'll own the full ML lifecycle and help shape the intelligent systems behind the factory of tomorrow.

What You'll Do

• Build and maintain ETL pipelines that turn raw scan, telemetry, and production data into something models can actually learn from
• Design, build, and maintain ML models and pipelines that solve real production and product problems
• Own the full lifecycle: data acquisition, feature engineering, training, deployment, monitoring, and iteration
• Integrate models into our software and production systems — they have to work in the real world, not just in notebooks
• Run experiments, evaluate honestly, and know when a model is good enough vs. when it isn't
• Collaborate with software engineers, hardware engineers, and product teams to translate ambiguous problems into ML solutions (and to recognize when ML isn't the right tool)
• Stay current with the field without chasing every new paper

Your profile

• Proven experience as an ML/AI Engineer, with models you've actually shipped to production
• Strong Python and fluency with the standard data/ML stack (NumPy, Pandas, scikit-learn)
• Solid ETL experience — designing and maintaining pipelines that handle real-world messy data at scale
• Hands-on deep learning experience with PyTorch and/or TensorFlow
• Solid grounding in ML fundamentals — you can explain why a model is failing, not just retrain it with different hyperparameters
• Software engineering discipline: clean code, version control, testing, and the ability to operate models you've built
• Cloud experience (AWS or GCP)
• As a company specializing in both hardware and software, we value close collaboration within our team. Therefore, we are seeking candidates who can join us at our office in Hamburg.

Nice To Have

• Computer Vision experience — directly relevant to scanning, quality control, and production
• NLP, especially applied to internal tools or customer-facing experiences
• MLOps in practice (Docker, Kubernetes, CI/CD for models, monitoring/drift detection)
• Experience working with sensor, telemetry, or manufacturing data
• Open-source contributions in the ML space