Senior Machine Learning Engineer

Job description

# Senior Machine Learning Engineer (m/w/d) – Freelance (PJ), Brazil 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.**