CarOnSale

Senior Machine Learning Engineer at CarOnSale (Brazil)

CarOnSale· Brazil·

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.

Why work at CarOnSale

  • Culture: Values include Boldness, Customer-centricity, Bias for action, Data driven, Ownership, and ONE Team mindset. Hands-on, entrepreneurial, and resilient environment.
  • Benefits: Competitive compensation + stock option program; mobility package (job bike, Deutschlandticket, company car for sales); health & wellbeing (Urban Sports Club or FitX membership); employer-sponsored retirement plan; employee shopping discounts; regular team events (summer event, COS Talks).
  • Work Model: Offices in Berlin (HQ), Munich, Nuremberg, and Hamburg. Hybrid/office policy likely varies by role (vehicle inspectors on road, field sales, tech roles in offices).
  • Hiring Process: CV submission → screening call with People Team → interview(s) with hiring team (may include task or case study) → offer. Typically 1–2 weeks decision time.
  • Engineering Culture: Tech stack is modern (specifics not detailed but noted on careers page); data-driven approach is core to the product and company mindset.

Application questions