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# Machine Learning Engineer

- **Company:** Akkodis
- **Location:** Madrid, Spain
- **Contract:** Permanent contract
- **Skills:** Agile Methodology, Artificial Intelligence, Software Quality, Code Review, Computer Programming, Continuous Integration, Data Cleansing, Software Debugging, DevOps, Monitoring of Systems, Python (Programming Language), Machine Learning, Tensorflow, Software Construction, Software Deployment, Working Model 2D, Cloud Platform System, Feature Engineering, Pytorch, Retrieval-Augmented Generation, Large Language Models, Multi-Agent Systems, Prompt Engineering, Model Validation, Generative AI, Kubernetes, Information Technology, Software Version Control
- **Published:** August 11, 2026
- **Apply:** https://es.trabajo.org/oferta-5001-67df6aef04a69918541769568adc87fe

## About the Role

metrics, benchmark datasets, and evaluation techniques. Continuously iterate and improve AI models based on performance analysis and business feedback. Collaboration & Integration Collaborate with Platform Teams, Data Engineers, Data Scientists, and business stakeholders to integrate AI solutions into enterprise systems. Participate in code reviews, testing, debugging, and continuous improvement initiatives. Contribute to the development of scalable, maintainable, and high-quality AI applications following software engineering best practices. ️ Engineering Excellence Apply DevOps principles throughout the AI development lifecycle. Ensure code quality through testing, documentation, version control, and continuous integration practices. Troubleshoot and resolve technical issues while maintaining reliable production environments. Your profile Bachelor's or Master's degree in Computer Science, Data Science, Mathematics, Statistics, or a related
field. Proven experience as a Machine Learning Engineer, Data Scientist, or similar AI-related role. Strong programming skills in Python . Hands-on experience with Machine Learning frameworks such as TensorFlow or PyTorch . Proven experience working with Large Language Models (LLMs) . Good understanding of AI Agents, Agentic Workflows, LLM orchestration frameworks, and reasoning patterns. Experience designing and implementing RAG (Retrieval-Augmented Generation) solutions. Strong knowledge of data preprocessing, feature engineering, model selection, and evaluation techniques. Solid understanding of statistical and mathematical concepts related to Machine Learning. Experience applying software development best practices, including version control, testing, and documentation. Strong analytical, troubleshooting, and problem-solving skills. Excellent communication and collaboration skills, with the ability to work effectively in
international and cross-functional teams. Continuous learning mindset and passion for emerging AI technologies. Attention to detail and commitment to delivering reliable, scalable, and maintainable solutions. High level of English (international working environment). Nice to have Experience working in Agile and DevOps environments. Experience building production-ready AI applications. Knowledge of AI evaluation frameworks and model monitoring. Experience deploying AI solutions in cloud environments. Financial services or banking industry experience. What we offer Hybrid working model. International and multicultural environment. Opportunity to work with the latest AI technologies, LLMs, Multi-Agent Systems, and Generative AI. Participation in innovative, enterprise-scale AI projects. Continuous learning, certifications, and professional development. Competitive salary according to your experience. If you're
passionate about Artificial Intelligence, Machine Learning, and Generative AI , and you're looking to work on innovative international projects where you can make a real impact, we'd love to hear from you Let's talk

## Description

with Data Scientists, Data Engineers, Platform Teams, and Software Engineers, you will contribute throughout the entire AI lifecycle-from concept and experimentation to production deployment-helping build scalable, reliable, and production-ready AI systems. Main responsibilities AI & Machine Learning Development Design, develop, deploy, and optimize Machine Learning and AI solutions for complex business use cases. Build multi-agent systems and develop AI solutions with function/tool-calling capabilities. Design and implement Retrieval-Augmented Generation (RAG) architectures using enterprise data. Evaluate, integrate, and optimize Large Language Models (LLMs) to ensure high performance and reliability. Optimize AI agents and agentic workflows for production environments. LLMs & Prompt Engineering Design, test, and optimize system prompts and few-shot examples to improve AI accuracy, consistency, and safety. Evaluate AI model performance using appropriate


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