Machine Learning Engineering Specialist

📋 Description

• Design system architecture to train, retrain, monitor, and serve ML models.
• Design, develop, and maintain scalable infrastructure for ML pipelines and APIs.
• Implement and manage CI/CD for ML model deployment and monitoring.
• Collaborate with data scientists and engineers to productionize ML models.
• Ensure security and privacy compliance in payment systems.
• Troubleshoot, optimize ML production systems for performance and scalability.

🎯 Requirements

• MLOps/DevOps experience.
• Cloud platforms: AWS, GCP, Azure.
• Docker and Kubernetes.
• ML frameworks: TensorFlow, PyTorch, Scikit-learn.
• Strong Python and CI/CD tools (Jenkins, GitHub Actions).
• Data pipelines/ETL and ML monitoring.

🎁 Benefits

• Performance Bonus: annual bonus program based on results.
• Meal Allowance: monthly meals allowance.
• EBANX Education: financial assistance for degrees.
• EBANX Skills: budget for courses and certifications.
• Language Classes: language learning support.
• Health & Well-being: medical and dental plans with dependents.