Senior Machine Learning Engineer
Verfasst am 2026-10-03
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IT/Informationstechnik
Maschinelles Lernen, Dateningenieur, Künstliche Intelligenz Ingenieur, Cloud Computing: IT-Infrastruktur & Betrieb
At PDR.cloud, 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.
Activities- PDR.cloud is a Berlin-based SaaS company enabling fully digital workshops for automotive repair shops — with modern IT architecture and smart solutions for complex damage processes
- 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
Must-have
- 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
Nice-to-have
- 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.
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