Machine Learning Engineer (m/f/x)

Jackalope Digital LLC

Berlin

Hybrid

EUR 90.000 - 130.000

Vollzeit

Vor 4 Tagen
Sei unter den ersten Bewerbenden

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Benefits dieser Stelle

Hybrid work 3 days in office / 2 days
28 days annual leave
Deutschlandticket (public transport)
Pension with employer contribution
Stock options
Buddy onboarding & social events

Zusammenfassung

CarOnSale, Europas AI-powered platform for used car trading, seeks a Senior Machine Learning Engineer in Berlin to own packaging, deployment, drift detection and model readiness for production.

You will work on a shared platform using SageMaker, Snowflake, Terraform on AWS, focusing on serving, monitoring and evaluation across models in a hybrid work setup.

Qualifikationen

  • 2+ years in production machine learning engineering with ownership after handoff.
  • Strong Python: typed, tested, production-grade code.
  • Sufficient ML depth to challenge pipeline design and evaluation.
  • Hands-on with a managed ML platform (SageMaker/Vetex AI/Databricks/Azure ML) plus feature stores, CI/CD, AWS/Terraform.
  • An AI-native working style using Claude, ChatGPT or Copilot.
  • English at C1 level; German not required.

Aufgaben

  • Own models from handoff through to production: packaging, deployment, monitoring, and readiness decisions.
  • Maintain production model reliability: drift detection, performance monitoring, alerting, incident response.
  • Own serving and inference path: pipeline artifacts, entry points, monitoring hooks, feature-store parity.
  • Review model design and evaluation methodology before shipping to catch data leakage and errors.
  • Extend the shared platform to stay useful for all models and prevent leakage of project-specific logic.
  • Set engineering standards for platform at scale across the organisation.

Kenntnisse

Production ML engineering
Python (typed, tested)
ML depth for feature engineering
Managed ML platforms (SageMaker, etc.)
CI/CD for ML / Terraform / AWS
English (C1)

Tools

SageMaker
Vertex AI
Databricks
Azure ML
Feature stores
CI/CD for ML
AWS
Terraform

Jobbeschreibung

Senior Machine Learning Engineer (m/w/d)

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.

One Platform. One Profit Engine.

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 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
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

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