ml engineer for automotive repair

Haystack is a fast-growing technology company developing a cloud-based SaaS platform that helps automotive repair shops manage complex damage processes more easily, quickly, and digitally.

• Take ownership of the entire ML lifecycle, from exploratory data analysis and model development to production pipelines and ongoing evaluation;
• Work hands-on as the first ML hire on the team, shaping data-driven intelligence;
• Collaborate with Product and Engineering using rapid prototyping to validate hypotheses and iterate on models;
• Extract insights from data and turn them into real product decisions;
• Calibrate models for a growing, heterogeneous customer base and continuously improve model quality;
• Work with modern IT architecture and smart solutions for complex damage processes.

• Several years of experience as a Machine Learning Engineer, Data Engineer, or Applied Data Scientist with a clear engineering focus;
• Strong Python and SQL skills;
• Confident use of a cloud platform such as AWS, GCP, or Azure;
• Solid statistical foundation beyond sklearn defaults;
• Understanding of classical and probabilistic model families;
• Experience with production model deployment and MLOps fundamentals;
• Ability to build new model pipelines from scratch;
• Pragmatic, hands-on mindset with experience in rapid prototyping and delivering MVPs;
• Ability to handle incomplete data and shifting requirements with confidence.

• Opportunity to be the first ML hire, shaping architecture, tooling, and data culture in a greenfield setup;
• Maximum creative freedom and real impact on product decisions;
• Flat hierarchies and short decision-making paths;
• Remote-friendly culture with regular team workshops and events in Berlin.