Machine Learning Engineer – Mid/Senior

This is a fully remote position, open to applicants anywhere in the world.

📋 Description

• Create tabular machine learning models aimed at operational decision-making, including risk classification (XGBoost), dynamic pricing (gradient boosting), and combinatorial assignment optimization (Google OR-Tools).

• Run models in shadow mode with human-in-the-loop (HITL) validation prior to any automation implementation.

• Develop the MLOps pipeline: training in Azure ML, model registry in MLflow, and inference deployment (FastAPI/Docker) on AWS, including environment promotion and rollback.

• Establish metrics and conduct backtesting with point-in-time accuracy utilizing the Feature Store.

• Execute drift monitoring, automated retraining, and canary/A-B deployment through CI/CD.

• Provide models via low-latency inference APIs (online features in Redis), supported by OpenAPI contracts.

⛳️ Requirements

• Bachelor's degree in Data Science, Computer Science, Statistics, Engineering, Mathematics, Economics, or a related discipline.

• Proficiency in English or Spanish (for international clients).

• Strong Python programming skills for production machine learning (beyond just notebooks).

• Experience with tabular models utilizing gradient boosting (XGBoost or similar), including imbalanced classification, probability calibration, and regression.

• Model assessment and backtesting expertise: AUC/Recall/Precision, MAPE/MAE/RMSE, as well as temporal validation and point-in-time accuracy.

• MLOps experience: model versioning and registry (MLflow or equivalent), training/deployment pipelines in CI/CD, along with environment promotion and rollback.

• Model serving through API (FastAPI or equivalent) within Docker containers.

• Proficient in SQL for data extraction and preparation.

🏝️ Benefits

• Contractor — PJ (we seek long-term partnerships).

• Option for remote work.

• Working hours: 8 hours daily (168 hours monthly).

• Time bank with quarterly settlement (payment for positive balance hours).

• Variable compensation available after 4 months of contract.

• Flexible benefits card: BRL 700.00 monthly for meals (Flash card).

• Paid leave: 7 consecutive days after 1 year of contract; 15 days after 2 years; 21 days between 5 and 7 years; and 30 days from 8 years onward.

• Birthday day off: one day off during your birthday month.

• Partnership with Wellhub.

• Partnership with Open English.

• Partnership with FIAP.

• Collaborations with clinics and psychological services.