Data Science & Machine Learning Engineer

About the Role ETAP’s Cloud Division is expanding its AI/ML capabilities and is seeking a Data Science & Machine Learning Engineer to help design, build, and deploy intelligent systems at scale. This hybrid role bridges data science and production engineering, focusing not only on building high-performing models but also on operationalizing them in real-world environments. You will work on high-impact initiatives across predictive modeling, graph machine learning, and generative AI, contributing directly to product innovation.

What You'll Do

• Design, develop, and deploy machine learning models for classification, regression, ranking, and recommendation systems
• Build end-to-end ML pipelines, from data ingestion and feature engineering to model deployment and monitoring
• Productionize models as scalable APIs using FastAPI, Docker, and cloud platforms (Azure ML)
• Implement robust validation, testing, and monitoring to ensure model performance and reliability in production
• Collaborate with data engineers and software teams to integrate ML solutions into production systems
• Monitor models for drift, retrain pipelines, and continuously improve performance

What We're Looking For

• Strong programming skills in Python, with expertise in Pandas, NumPy, and scikit-learn
• Experience building and deploying end-to-end ML systems in production environments
• Solid knowledge of SQL/NoSQL databases and data pipeline development
• Hands-on experience with XGBoost and/or LightGBM for structured data problems
• Experience with MLOps tools such as Git, Docker, MLflow/Weights & Biases, and Azure ML
• Strong understanding of model evaluation metrics and performance trade-offs

Nice to Have

• Experience with deep learning frameworks (PyTorch or TensorFlow)
• Familiarity with model optimization and tuning (e.g., Optuna)
• Experience with Graph ML (PyTorch Geometric, DGL) or Generative AI (RAG, embeddings, LangChain, LlamaIndex)
• Knowledge of model serialization and deployment standards (ONNX)
• Experience working in cloud-native, distributed environments

Compensation & Benefits

• Competitive compensation aligned with the Mexican market
• Opportunity to work on cutting-edge AI/ML and cloud technologies
• A collaborative, innovative, and inclusive work environment
• Exposure to global teams and impactful projects