Job Summary: We are seeking an MLOps Engineer / Machine Learning Engineer with experience in production environments to take machine learning models from development through deployment, monitoring, and evolution. Key Highlights: 1. Stable project in AI and advanced analytics 2. Work with cutting-edge technologies in cloud, data, and machine learning 3. Collaborative and continuously evolving technical environment **Description:** ---------------- What are we looking for? We seek an MLOps Engineer / Machine Learning Engineer with experience in production environments, capable of taking machine learning models from development through deployment, monitoring, and evolution. You will join a technical team working on advanced analytics and artificial intelligence projects, with a focus on model industrialization and data platforms. **What will you do daily?** Development and deployment of machine learning solutions in production Design and maintenance of data pipelines and automated processes Management of containerized environments (Docker) and orchestration (Kubernetes) Implementation of CI/CD for ML models Model monitoring (drift, retraining, performance) Work with cloud platforms (AWS, Azure, or GCP) Optimization and administration of data platforms (especially Stratio) **What do we offer?** A stable, long-term project in AI and advanced analytics environments Work with cutting-edge technologies in cloud, data, and machine learning A collaborative and continuously evolving technical environment Flexible work modality (hybrid/remote) Competitive salary commensurate with experience **Requirements:** --------------- * University degree in Computer Engineering, Telecommunications, Mathematics, or another STEM discipline * At least 3 years of experience in: Machine Learning, Data Engineering, or MLOps **Key Technologies:** * Python applied to ML or data * Docker and Kubernetes * CI/CD and pipeline automation * Git and experimentation tools (MLflow or similar) * Cloud (AWS, Azure, or GCP) * Production model monitoring **Highly Important:** Experience in: * Model retraining * Drift management * Production model operations **Project-Specific Requirement:** Experience with the Stratio platform (minimum 3 years) * Configuration * Administration * Optimization **Desirable Qualifications:** * Experience with MLOps and pipeline orchestration tools (e.g., Kubeflow, Airflow, MLflow, or similar) * Knowledge of large-scale data processing (e.g., Spark or distributed environments) * Experience in microservice architectures and APIs for AI models * Knowledge of model governance, explainability, and drift control * Experience in machine learning industrialization projects (taking models into production) * Knowledge of DevOps practices applied to data and artificial intelligence Our commitment is to foster workplaces where individuals are treated with respect and dignity, always supporting the professional development of all employees. We guarantee equal opportunities throughout selection, training, and promotion processes, offering a work environment free from any form of discrimination based on gender, age, disability, sexual orientation, gender identity or expression, marital status, or personal or social circumstances. This position is open to all candidates meeting the job requirements. Candidates holding a disability certificate of 33% or higher, as defined by the General Law on the Rights of Persons with Disabilities (LGD), will be especially valued.