ML Engineer - IA / Data

Professional experience as an ML Engineer, Machine Learning Engineer, MLOps Engineer, or in similar positions.

Experience with Python.

Knowledge and experience with Machine Learning / Deep Learning frameworks.

Experience in development and integration via APIs.

Experience with Docker and Kubernetes.

Knowledge of CI/CD and deployment automation.

Experience or knowledge of MLOps / LLMOps.

Knowledge of Cloud environments.

Experience with testing and automation.

Knowledge of feature stores, model registries, and dataset/experiment management.

Knowledge of model observability and monitoring.

Experience in inference and performance optimization is valued.

Experience in generative Artificial Intelligence and LLM solutions is valued.

• Professional experience as an ML Engineer, Machine Learning Engineer, MLOps Engineer, or in similar positions.
• Experience with Python.
• Knowledge and experience with Machine Learning / Deep Learning frameworks.
• Experience in development and integration via APIs.
• Experience with Docker and Kubernetes.
• Knowledge of CI/CD and deployment automation.
• Experience or knowledge of MLOps / LLMOps.
• Knowledge of Cloud environments.
• Experience with testing and automation.
• Knowledge of feature stores, model registries, and dataset/experiment management.
• Knowledge of model observability and monitoring.
• Experience in inference and performance optimization is valued.
• Experience in generative Artificial Intelligence and LLM solutions is valued.

Hybrid work model in Madrid.

Permanent contract.

Stable, long-term technological project.

Participation in Machine Learning and Artificial Intelligence projects.

Technological environment oriented towards innovation and automation.

Opportunity for professional growth and development.

Continuous training plan.

Health insurance.

Dental insurance.

Restaurant tickets.

Nursery Check.

Continuous training plan.

At Infortec Consultores we continue to grow and are looking to hire an ML Engineer to participate in technological projects related to Machine Learning and Artificial Intelligence.

We are looking for a profile with experience in the industrialization and production deployment of Machine Learning models, capable of transforming prototypes and experimental models into reliable, secure, scalable, and maintainable solutions.

If you are interested in working on AI projects where engineering, automation, and production deployment play a key role, we want to meet you!

Package, deploy, and operate Machine Learning models in production environments.

Design and build training and inference pipelines.

Automate testing, versioning, and deployment processes.

Manage model registries, datasets, and experiments.

Implement model monitoring and observability solutions.

Monitor performance, quality, drift (model drift), and costs.

Optimize inference processes and infrastructure usage.

Implement rollback, retraining, and recovery mechanisms.

Work on model integration through APIs and services.

Apply MLOps and LLMOps best practices.

Collaborate with development, data, and infrastructure teams to take AI solutions from development to production.

If you want to take the next step in your career as an ML Engineer and work on projects where AI models truly reach production, this opportunity is for you.

Apply for this offer and send us your updated CV. We want to meet you!