Senior Machine Learning Engineer (m/f/x)

You don't want another contract that ends at the notebook. You want the pager, the promotion lane and the authority to say a model isn't ready. This one is based in Brazil, 40 hours a week on your own invoice, and everything after handoff is yours.

Location: Remote from Brazil — you must be based in Brazil. 40 hours per week, Monday to Friday, with daily overlap into the Berlin working day.

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. Four models serve production today. Fifteen to twenty by mid-2027. Your job is to build inside that platform 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

You are based in Brazil and invoice through your own company. We work directly with you, not through intermediary or umbrella services

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

A full-time engagement: 40 hours per week, Monday to Friday, invoiced monthly against your own company

You are treated like a full member of the team — standups, bi-weekly sprints, and all company communication

Fully remote from anywhere in Brazil

An English-speaking engineering team with short decision paths

Direct ownership of models serving a live product, not a proof of concept

Structured onboarding with a buddy from the team

Apply now — your CV is enough.