Senior Machine Learning Engineer

📋 Description

• You own models from handoff through to production: packaging, deployment, monitoring, and the
• You keep production models reliable — drift detection, performance monitoring, alerting and
• You own the serving and inference path: fitted pipeline artifacts, inference entry points
• You review model design and evaluation methodology before anything ships, and catch data leakage
• You extend the shared platform so it stays useful for every model, without project-specific logic
• You set the engineering standards the platform runs on as it scales across the organisation

🎯 Requirements

• 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 machine learning depth to challenge a pipeline on problem framing, feature engineering
• Hands-on experience with a managed ML platform — SageMaker, Vertex AI, Databricks or Azure ML —
• An AI-native way of working: you use tools like Claude, ChatGPT or Copilot actively in your daily
• English at C1 level, written and spoken. German is not required — we work in English

🎁 Benefits

• A full-time engagement: 40 hours per week, Monday to Friday, invoiced monthly against your own
• You are treated like a full member of the team — standups, bi-weekly sprints, and all company
• 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