Machine learning engineer in automotive SaaS

ud, we are digitalizing the workshop of the future. Since 2018, we have been developing a cloud-based SaaS platform from Berlin that helps automotive repair shops manage complex damage processes more easily, faster, and fully digitally. As a Senior Machine Learning Engineer ud, you will take ownership of the entire ML lifecycle — from exploratory data analysis and model development to production pipelines and ongoing evaluation.

You work hands‑on, are the first ML hire on the team, and shape what data‑driven intelligence looks like ud. Greenfield, real creative freedom, and bold pilot customers included.

As a Senior Machine Learning Engineer ud, you will own the complete ML lifecycle: exploratory analysis, data modeling, feature engineering, model development, and production pipelines. You work hands‑on across everything that comes with it — including data acquisition, schema design, data preparation, and the tools we use to evaluate our data. You collaborate closely with Product and Engineering using a rapid prototyping approach: validating hypotheses, iterating on models, extracting insights from data, and turning them into real product decisions.

The role ud offers maximum creative freedom: you shape architecture, tooling, and data culture. Beyond the prototyping phase, exciting long-term challenges await: you will calibrate our models for a growing, heterogeneous customer base and continuously improve model quality.

• Several years of experience as a Machine Learning Engineer, Data Engineer, or Applied Data Scientist with a clear engineering focus — you design pipelines yourself and solve data problems independently
• Strong Python and SQL skills, plus confident use of a cloud platform (AWS, GCP, or Azure)
• A solid statistical foundation beyond sklearn defaults: you know classical and probabilistic model families and understand when to apply which approach
• Experience with production model deployment and MLOps fundamentals — you don't need a ready‑made ML platform, but build new model pipelines from scratch together with our ops professionals ud
• A pragmatic, hands‑on mindset: you enjoy working in rapid prototyping mode, deliver MVPs instead of over‑engineered architecture, and handle incomplete data and shifting requirements with confidence
• Будет плюсом:
  Experience with event or sequence data (logs, tracking events, transaction data) and irregular timestamps;
  Knowledge of probabilistic modeling or process mining;
  Experience building data and ML infrastructure in a greenfield setup;
  Background in SaaS, automotive, or insurance environments;
  Experience in agile product teams and direct collaboration with pilot customers

You will be part of a dedicated, interdisciplinary development team of experienced fullstack developers, UX designers, and product managers. ud, open communication, mutual support, and a constructive feedback culture are what matter — you will feel that from day one. You will work primarily remote, but regularly join your team for workshops or team‑building events in Berlin — for shared ideas and genuine connection beyond the screen.

Flat hierarchies and short decision‑making paths give you the freedom you need to work creatively, efficiently, and independently, while continuing to grow personally.