Machine Learning Engineer (m/f/x)

Four models in production today. Fifteen to twenty by mid-2027. The shared pipeline that gets them there has to hold — and you own everything after handoff: packaging, deployment, drift detection, and the call on whether a model is fit to serve.

Location: Berlin Schöneberg — you work from our office, hybrid with 3 days office and 2 days home office.

About Us

CarOnSale is the AI-powered platform for B2B used car trading in Europe. Over 40,000 buyers from more than 20 countries trade on our platform — and 85% of inventory is exclusive to us. We connect software, pricing intelligence, logistics and financing in one layer — as the operating system for an entire industry.

The Platform You Build In

Our machine learning runs on one shared, central platform — not a separate pipeline per model. Five canonical stages: data extraction, validation, transformation, training and evaluation. A Snowflake data warehouse feeds a SageMaker managed feature store, and models reach production through governed CI/CD promotion lanes on Terraform-managed AWS infrastructure. Your job is to build inside it and make it stronger, so the next model costs less to ship than the last one.

Your Responsibilities

• You own models from handoff through to production: packaging, deployment, monitoring, and the decision on whether a model is ready to serve.
• You keep production models reliable — drift detection, performance monitoring, alerting and incident response.
• You own the serving and inference path: fitted pipeline artifacts, inference entry points, monitoring hooks and feature-store parity.
• You review model design and evaluation methodology before anything ships, and catch data leakage, backward-window errors and weak evaluation during development.
• You extend the shared platform so it stays useful for every model, without project-specific logic leaking into shared code.
• You set the engineering standards the platform runs on as it scales across the organisation.

What You Bring

• 2+ years in production machine learning engineering, with real ownership of models after handoff — not only training them.
• Strong Python: typed, tested, production-grade code, and you review the work of others.
• Enough machine learning depth to challenge a pipeline on problem framing, feature engineering, model selection and evaluation methodology.
• Hands-on experience with a managed ML platform — SageMaker, Vertex AI, Databricks or Azure ML — plus feature stores, CI/CD for machine learning, AWS and Terraform.
• An AI-native way of working: you use tools like Claude, ChatGPT or Copilot actively in your daily work.
• English at C1 level, written and spoken. German is not required — we work in English.

Nice to Have

• Snowflake and dbt — you can pick both up here.
• Experience mentoring colleagues or reviewing their work.
• Comfort operating where the answer is not defined yet.

What to Expect From Us

• Hybrid working: 3 days in office, 2 days remote – plus 25 "Work from Anywhere" days per year.
• 28 days annual leave.
• 2× annual career & development conversations.
• Company pension with 20% employer contribution.
• Fully paid Deutschlandticket (public transport).
• FitX membership or Urban Sports Club subsidy.
• Virtual stock options — share in the upside.
• Modern IT setup for your day-to-day work.
• Structured onboarding with buddy programme and social events.
• Lived diversity: active women's network, meditation & prayer room, dog-friendly office.

Apply now — your CV is enough.