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# MLOps / Data Scientist

- **Company:** Mlops
- **Location:** Madrid, Spain
- **Contract:** Permanent contract
- **Skills:** Data Analysis, Databases, Continuous Integration, Data Validation, DevOps, Python (Programming Language), Machine Learning, NoSQL, NumPy, Remote Administration, Tensorflow, SQL Databases, Pytorch, Deep Learning, Git, Pandas, Scikit Learn, Kubernetes, Machine Learning Operations, Software Version Control, Docker, Microservices
- **Published:** August 29, 2026
- **Apply:** https://www.recruit.net/job/mlops-data-scientist-jobs/0F33470A8EF48A49

## About the Role

* Conocimientos de infraestructura y entornos de computación en servidores físicos (bare metal).
 * Experiencia en contenedores y orquestación con herramientas como Kubernetes, Docker o similares.
 * Conocimientos de plataformas de Machine Learning y MLOps como Kubeflow, MLflow o herramientas equivalentes.
 * Experiencia en automatización CI/CD y prácticas DevOps.
 * Programación y automatización, principalmente en Python y SQL.
 * Arquitecturas de microservicios., * Desarrollo y Analítica Core: Dominio fluido de Python y librerías de análisis de datos (Pandas, NumPy)
 * Modelado: Experiencia práctica con librerías de Machine Learning clásico (Scikit-Learn) y Deep Learning (PyTorch o TensorFlow).
 * Infraestructura On-Premise: Manejo diario de Docker, gestión de entornos virtuales (venv, conda), conexión/administración básica de Bases de Datos (SQL/NoSQL) y administración remota vía SSH.
 * Calidad y MLOps Core: Experiencia con Great Expectations (para validación de datos) y herramientas de control de versiones/ciclo de vida como Git, DVC y Mlflow.

## Description

Estamos ampliando nuestro equipo y buscamos dos perfiles clave con más de 1 año de experiencia para impulsar nuestros proyectos de IA: un/a MLOps Engineer, enfocado/a en la industrialización y despliegue de modelos, y un/a Data Scientist, especializado/a en convertir los datos en soluciones innovadoras.


## Related Videos

- [Effective Machine Learning - Managing Complexity with MLOps](https://www.wearedevelopers.com/videos/185-effective-machine-learning-managing-complexity-with-mlops)
- [Vectorize all the things! Using linear algebra and NumPy to make your Python code lightning fast.](https://www.wearedevelopers.com/videos/562-vectorize-all-the-things-using-linear-algebra-and-numpy-to-make-your-python-code-lightning-fast)
- [Leveraging Real time data in FSIs](https://www.wearedevelopers.com/videos/806-leveraging-real-time-data-in-fsis)
- [How a Small Team Shrank a Microsoft Monorepo by 94%](https://www.wearedevelopers.com/videos/1236-how-a-small-team-shrank-a-microsoft-monorepo-by-94)
- [DevOps for Machine Learning](https://www.wearedevelopers.com/videos/179-devops-for-machine-learning)
- [How to implement convenient Python bindings to C++](https://www.wearedevelopers.com/videos/618-how-to-implement-convenient-python-bindings-to-c)

## Related Articles

- [MLops – Deploying, Maintaining And Evolving Machine Learning Models in Production](https://www.wearedevelopers.com/magazine/115-mlops-deploying-maintaining-and-evolving-machine-learning-models-in-production)
- [MLOps – What’s the deal behind it?](https://www.wearedevelopers.com/magazine/125-mlops-what-s-the-deal-behind-it)
- [MLOps And AI Driven Development](https://www.wearedevelopers.com/magazine/82-mlops-and-ai-driven-development)
- [How We Built a Worry-Free System That Runs for 10+ Years – And What We’d Do Again](https://www.wearedevelopers.com/magazine/751-how-we-built-a-worry-free-system-that-runs-for-10-years-and-what-we-d-do-again)
- [What Are Large Language Models?](https://www.wearedevelopers.com/magazine/304-what-are-large-language-models)
- [Everything a Developer Needs to Know About MCP with Neo4j](https://www.wearedevelopers.com/magazine/604-everything-a-developer-needs-to-know-about-mcp-with-neo4j)