Machine Learning Engineer - AWS SageMaker (LATAM)

Experience building production Machine Learning solutions using Amazon SageMaker (Processing, Training, Pipelines, Endpoints, Model Registry) Proficiency in Python for data and ML (pandas, numpy, scikit-learn) Experience with ML frameworks like XGBoost, LightGBM, PyTorch/TensorFlow Solid experience in MLOps (versioning, reproducibility, monitoring, drift detection, retraining) Deep knowledge of data preparation and data quality Experience in synthetic data generation Knowledge of AWS security and governance (IAM, KMS, audit, access control) Ability to work under agile methodologies Clear communication and documentation skills

Design and implement the complete Machine Learning pipeline in Amazon SageMaker Build data preparation processes (cleaning, normalization, imputation, validation) Define and operate a Feature Store in SageMaker Implement feature engineering with controls Train and evaluate regression models Manage model versioning and lifecycle using SageMaker Model Registry Deploy inferences using SageMaker Endpoints and/or APIs Implement model monitoring with SageMaker Model Monitor Define and operate ground truth processes Design and implement synthetic data strategies Validate synthetic data Implement automated data quality controls and pipeline observability Participate in technical estimation of ML/MLOps backlog Document architecture, technical decisions, and standards