Machine Learning Engineer (m/f/x)

Meyandy LLC; Berlin; Hybrid; EUR 90.000 - 120.000; Vollzeit

Benefits dieser Stelle

Hybrid work: 3 days in office, 2 days

25 Work from Anywhere days

28 days annual leave

Company pension with 20% employer

Deutschlandticket

Fitness club subsidy

Stock options

Modern IT setup

Structured onboarding

Diversity network

Zusammenfassung

CarOnSale is hiring a Senior Machine Learning Engineer to own models from handoff to production, including packaging, deployment, monitoring and drift detection. You will ensure reliable serving and governance within a shared platform used across models.

The role requires deep ML expertise, strong Python, and experience with managed platforms like SageMaker, Vertex AI, Databricks or Azure ML. English is the working language; German is not required.

Qualifikationen

• 2+ years in production machine learning engineering, with real ownership of models after handoff.
• Strong Python: typed, tested, production-grade code, and you review the work of others.
• Enough ML 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 ML, 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.

Aufgaben

• 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

Kenntnisse

Production ML engineering

Python

SageMaker

Vertex AI

Databricks

Azure ML

Feature stores

CI/CD for ML

AWS

Terraform

Claude

ChatGPT

Copilot

English (C1)

Tools

SageMaker

Vertex AI

Databricks

Azure ML

Feature stores

CI/CD for ML

AWS

Terraform

Claude

ChatGPT

Copilot

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 offic…