MLOps Engineer / Machine Learning Engineer

Description

Job Summary: We are seeking an MLOps Engineer / Machine Learning Engineer with experience to take machine learning models from development through deployment, monitoring, and evolution. Key Highlights: 1. Stable and long-term project in AI and advanced analytics environments 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 experienced MLOps Engineer / Machine Learning Engineer with production environment expertise, 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, focusing on model industrialization and data platforms. **What will you do daily?** Developing and deploying machine learning solutions in production Designing and maintaining data pipelines and automated processes Managing containerized environments (Docker) and orchestration (Kubernetes) Implementing CI/CD for ML models Monitoring models (drift, retraining, performance) Working with cloud platforms (AWS, Azure, or GCP) Optimizing and administering data platforms (especially Stratio) **What do we offer?** Stable and long-term project in AI and advanced analytics environments Work with cutting-edge technologies in cloud, data, and machine learning Collaborative and continuously evolving technical environment Flexible work arrangement (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 (e.g., MLflow or similar) * Cloud (AWS, Azure, or GCP) * Monitoring of models in production **Highly Important:** Experience in: * Model retraining * Drift management * Operating models in production **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 microservices architectures and APIs for AI models * Knowledge of model governance, explainability, and drift control * Experience in machine learning industrialization projects (taking models to production) * Understanding 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, providing 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.