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Machine Learning Engineer (m/f/x)CarOnSale · Berlin, Germany
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CarOnSale

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Machine Learning Engineer (m/f/x)

🗓️ Posted 2026-09-15 Berlin, Germany Hybrid ICT
💰 Salary Not shared 📊 Market 4,583 EUR–6,667 EUR/mo

About the Company

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. One Platform. One Profit Engine.

About the Role

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. 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.

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 when something moves
  • ● 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, while they are still cheap to fix
  • ● 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

Requirements

  • ● 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
  • ● 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

Benefits

  • ● Hybrid working: 3 days in office, 2 days remote - plus 25 "Work from Anywhere" days per year
  • ● 28 days annual leave