> Markdown version of [/jobs/ext/3085212-ai-ml-engineer](https://www.wearedevelopers.com/jobs/ext/3085212-ai-ml-engineer). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md).

---

# Ai /Ml Engineer

- **Company:** Hewlett-Packard
- **Location:** Barcelona, Spain
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Computer Programming, Continuous Integration, Machine Learning, Software Deployment, Software Systems, Information Technology, Machine Learning Operations
- **Published:** September 26, 2026
- **Apply:** https://www.buscojobs.com.es/ai-ml-engineer-en-barcelona-ID-372980872

## About the Role

This is an opportunity to shape automated ML capabilities and deliver impactful AI solutions at scale.Compensaciones / Beneficios - Develop integrated software solutions supporting the ML model life cycle - Train, validate, and evaluate models using appropriate metrics - Tune hyperparameters to improve performance and generalization - Deploy ML models to production ensuring scalability and reliability - Monitor and update deployed models to adapt to data changes - Lead design of ML systems and experiments for efficiency - Design, develop, test, and maintain ML pipelines for scalable models - Collaborate with CI/CD teams for smooth production deployment - Partner with research and engineering teams to enhance automated training techniques - Apply ML and statistical modeling to business or research problemsResponsabilidades - Four-year or graduate degree in Computer Science, Statistics, Mathematics, Data Science, or related discipline or equivalent experience - Typically 4-7
years of work experience in programming, ML, algorithms, or related field - Strong programming and ML fundamentals - Experience with ML pipelines and model deployment (productionization)Requisitos principales -

## Description

Experteer Overview In this role you will specialize in developing and deploying machine learning models that drive business value.You'll work with cross-functional teams to research, train, and productionize models, and ensure seamless integration into production systems.You'll design scalable ML pipelines, tune models for performance, and monitor deployed systems to adapt to evolving data.This is an opportunity to shape automated ML capabilities and deliver impactful AI solutions at scale.Compensaciones / Beneficios - Develop integrated software solutions supporting the ML model life cycle - Train, validate, and evaluate models using appropriate metrics - Tune hyperparameters to improve performance and generalization - Deploy ML models to production ensuring scalability and reliability - Monitor and update deployed models to adapt to data changes - Lead design of ML systems and experiments for efficiency - Design, develop, test, and maintain ML pipelines for scalable models - Collaborate with CI/CD teams for smooth production deployment - Partner with research and engineering teams to enhance automated training techniques - Apply ML and statistical modeling to business or research problemsResponsabilidades - Four-year or graduate degree in Computer Science, Statistics, Mathematics, Data Science, or related discipline or equivalent experience - Typically 4-7 years of work experience in programming, ML, algorithms, or related field - Strong programming and ML fundamentals - Experience with ML pipelines and model deployment (productionization)Requisitos principales -


## Related Videos

- [Introduction to Azure Machine Learning](https://www.wearedevelopers.com/videos/368-introduction-to-azure-machine-learning)
- [Rethinking Intelligence: AI, Accessibility, and the Future of Inclusive Work - Artur Ortega](https://www.wearedevelopers.com/videos/1377-rethinking-intelligence-ai-accessibility-and-the-future-of-inclusive-work-artur-ortega)
- [Charting the Journey to Continuous Deployment with a Value Stream Map](https://www.wearedevelopers.com/videos/142-charting-the-journey-to-continuous-deployment-with-a-value-stream-map)
- [Effective Machine Learning - Managing Complexity with MLOps](https://www.wearedevelopers.com/videos/185-effective-machine-learning-managing-complexity-with-mlops)
- [How Machine Learning is turning the Automotive Industry upside down](https://www.wearedevelopers.com/videos/61-how-machine-learning-is-turning-the-automotive-industry-upside-down)
- [What non-automotive Machine Learning projects can learn from automotive Machine Learning projects](https://www.wearedevelopers.com/videos/397-what-non-automotive-machine-learning-projects-can-learn-from-automotive-machine-learning-projects)

## Related Articles

- [How to Become an AI Engineer](https://www.wearedevelopers.com/magazine/331-how-to-become-an-ai-engineer)
- [MLOps – What’s the deal behind it?](https://www.wearedevelopers.com/magazine/125-mlops-what-s-the-deal-behind-it)
- [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 And AI Driven Development](https://www.wearedevelopers.com/magazine/82-mlops-and-ai-driven-development)
- [What Are Large Language Models?](https://www.wearedevelopers.com/magazine/304-what-are-large-language-models)
- [What Industries Outside of AI Are Hiring The Most AI Experts?](https://www.wearedevelopers.com/magazine/98-what-industries-outside-of-ai-are-hiring-the-most-ai-experts)