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Senior Machine Learning Engineer
Haystack · Berlin
Berlin · RemoteFull-TimePosted Aug 25, 2026
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Free · no credit card · 30 secondsJob description
A fast-growing tech company is disrupting the automotive repair industry by developing a cloud-based SaaS platform that helps repair shops manage complex damage processes more easily, faster, and fully digitally. They are seeking a highly skilled individual to drive their data-driven intelligence.
The Role
- Take ownership of the entire ML lifecycle, from exploratory data analysis and model development to production pipelines and ongoing evaluation
- Work hands-on, shaping the data-driven intelligence as the first ML hire on the team
- Collaborate closely with Product and Engineering using a rapid prototyping approach to validate hypotheses and iterate on models
- Extract insights from data and turn them into real product decisions, with maximum creative freedom
- 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
What You'll Need
- 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, plus confident use of a cloud platform (AWS, GCP, or Azure)
- Solid statistical foundation beyond sklearn defaults, understanding classical and probabilistic model families
- Experience with production model deployment and MLOps fundamentals, able to build new model pipelines from scratch
- Pragmatic, hands-on mindset, enjoying rapid prototyping and delivering MVPs
- Ability to handle incomplete data and shifting requirements with confidence
What's On Offer
- 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/events in Berlin
Apply via Haystack today!
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