Ingeniero en Inteligencia Artificial, Ciberseguridad – MLSecOps

This is a fully remote position, open to applicants in Chile.

📋 Description

• Design, train, and validate Machine Learning / Deep Learning models focused on network anomaly detection, user behavior (UEBA), and complex fraud patterns.

• Package, deploy, and scale analytical models within the production environments of the security management team.

• Integrate models with data ingestion workflows and ensure traceability throughout the model lifecycle.

• Monitor the performance of models in production, identifying deviations (model drift) and making periodic adjustments.

• Maintain versioning, documentation, and complete traceability of all production models, ensuring an auditable and reproducible lifecycle.

⛳️ Requirements

• Hold a degree in Civil Computer Engineering, Computer Engineering, Statistics, Mathematics, Physics, or a related field with a strong quantitative and computational component.

• Have 2 to 4 years of experience in Data Science, MLOps, or Machine Learning Engineering roles.

• Demonstrate strong competencies in data handling and machine learning models (regressions, classifications).

• Possess exclusive proficiency in AI/ML languages and frameworks such as Python, TensorFlow, PyTorch, Scikit-learn, Numpy, and CuPy.

• Have proven practical experience in MLOps environments such as MLflow, Kubeflow, Amazon SageMaker, Azure Machine Learning, or Vertex AI.

• Exhibit advanced proficiency in data processing (SQL, Pandas) and model evaluation metrics such as Precision, Recall, F1-Score, AUC-ROC, and AUC-PR.

🏝️ Benefits

• Annual budget for self-managed training.

• Remote work options.

• Day off for your birthday.

• Half-day off for children’s or parents’ birthdays.

• Short Fridays (we finish at 2 PM every Friday).

• Work from anywhere (Work from wherever you like! Just remember to have a good internet connection).