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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 at PDR.cloud, 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 at PDR.cloud. 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 at PDR.cloud, 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 at PDR.cloud 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

Requirements

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 at PDR.cloud
• 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

Team

You will be part of a dedicated, interdisciplinary development team of experienced fullstack developers, UX designers, and product managers. At PDR.cloud, 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.

Application Process

Our application process is transparent, streamlined, and personal:

1. Initial introduction (remote) — A brief conversation to get to know you and your motivation.
2. Technical interview — A technical discussion with our developers, potentially including a code review or a small practical task.
3. Team interview — An exchange with your future colleagues to ask questions and get a feel for our working environment.
4. Final conversation & offer — A joint alignment on the terms and your earliest possible start date.

We value prompt feedback and will support you throughout the entire process in an open and appreciative way.