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# AI/ML Engineer

- **Company:** Talantir
- **Location:** Barcelona, Spain
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Algorithm Design, Amazon Web Services, Artificial Neural Networks, Computer Vision, Microsoft Azure, Big Data, Data Governance, High-Level Architecture, Machine Learning, Tensorflow, Google Cloud, Cloud Platform System, Feature Engineering, Pytorch, Deep Learning, Data Strategy, Scikit Learn, Information Technology, Machine Learning Operations, Software Version Control
- **Published:** October 25, 2026
- **Apply:** https://www.jobleads.com/es/job/ai-ml-engineer--barcelona--ea43059d60b2e59829e36e4d3ba334863

## About the Role

* Bachelor's degree (or higher) in Computer Science, Data Science, Mathematics, or a related field.
 * Proven experience in the development and deployment of machine learning models (e.g., NLP, computer vision, or predictive analytics).
 * Strong background in statistical analysis and algorithmic characterization.
 * Hands-on experience with ML testing techniques and frameworks (e.g., PyTorch, TensorFlow, Scikit-learn).
 * Ability to design and execute data experiments, interpret complex datasets, and draw actionable conclusions.
 * Proficiency in technical reporting and the ability to communicate AI results to both technical and non-technical stakeholders.
 * Knowledge of MLOps practices, model versioning, and process-data interactions.
 * Familiarity with cloud computing platforms (AWS, Azure, GCP) or simulation tools for testing model behavior.
 * Experience with data quality systems and AI ethics/qualification frameworks (e.g., ISO standards or industry-specific regulations).

## Description

We are seeking a highly motivated AI/ML Engineer to join our team in Spain. This is a permanent position offering the opportunity to work at the forefront of artificial intelligence and machine learning innovation.

The successful candidate will play a key role in the development, training, and optimization of models, with a focus on enhancing algorithmic performance and predictive accuracy for demanding engineering applications. You will be part of a multidisciplinary team developing intelligent systems and automated solutions from concept through to production. This role offers long-term career growth and the opportunity to shape the digital transformation and data-driven strategy of innovative platforms.

All applicants must be eligible to work in Spain.

Responsibilities / What You Will Do

 * Lead and support the development of new machine learning models, with an emphasis on deep learning, neural networks, and advanced algorithms.
 * Characterize and optimize model performance metrics (e.g., accuracy, precision, recall, latency, and scalability).
 * Conduct experimental testing and analysis of large datasets, feature engineering, and model architectures.
 * Collaborate with software engineers and product teams to ensure model performance aligns with end-use applications and production environments.
 * Develop and maintain ML pipelines, data standards, and automated testing frameworks for model qualification.
 * Support R&D projects, contributing to technical reports, publications, and presentations on AI advancements.
 * Stay current with emerging AI research, frameworks, and industry standards in machine learning and data science.

Experience / Who You Are

 * Bachelor's degree (or higher) in Computer Science, Data Science, Mathematics, or a related field.
 * Proven experience in the development and deployment of machine learning models (e.g., NLP, computer vision, or predictive analytics).
 * Strong background in statistical analysis and algorithmic characterization.
 * Hands-on experience with ML testing techniques and frameworks (e.g., PyTorch, TensorFlow, Scikit-learn).
 * Ability to design and execute data experiments, interpret complex datasets, and draw actionable conclusions.
 * Proficiency in technical reporting and the ability to communicate AI results to both technical and non-technical stakeholders.
 * Knowledge of MLOps practices, model versioning, and process-data interactions.
 * Familiarity with cloud computing platforms (AWS, Azure, GCP) or simulation tools for testing model behavior.
 * Experience with data quality systems and AI ethics/qualification frameworks (e.g., ISO standards or industry-specific regulations).