Machine Learning Engineer

About the role

, GCP) and containerization technologies (Docker, Kubernetes) is a plus. Key missions: Contribuir al desarrollo de algoritmos y modelos de aprendizaje automático para la modelización del comportamiento y la detección de ataques cibernéticos.. Trabajar con equipos multifuncionales para comprender los requisitos y traducirlos en soluciones efectivas de aprendizaje automático.. Participar en la revisión de código para garantizar la calidad y mantenibilidad de los sistemas de aprendizaje automático. Profile: - The ideal candidate will have a background in machine learning, data science, and software engineering, with the ability to design, develop, and implement robust machine learning models and systems in production - Awareness of machine learning operations (MLOps) and productionization of ML models best practise. - Ability to communicate technical ideas in a clear, non-technical manner - Familiarity with building data and metric generation pipelines, using tools like SQL or Spark, to answer business questions and assess system efficacy - Proven experience as a Machine Learning Engineer or similar role in a commercial environment (3+ years) - Proficiency with Python and machine learning toolkits like pandas, scikit-learn, and optionally. pytorch/tensorflow - Knowledge of machine learning algorithms, statistics, and predictive modeling - Familiarity with LLMs - Previous experience in Cybersecurity - Previous experience with Airflow or similar ML pipeline orchestration tools - Previous experience in behavioural modeling techniques - Experience with large scale ML system and data infrastructure - PhD or equivalent proven experience in ML research - Familiarity with cloud computing platforms (AWS, Azure