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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Senior Data Science Engineer - **Company:** N-iX - **Location:** Spain (Remote available) - **Contract:** Permanent contract - **Skills:** Agile Methodology, Artificial Intelligence, Business Logic, Computer Programming, Data Mining, Data Structures, Graph Database, JSON, Python (Programming Language), Machine Learning, Natural Language Processing, NoSQL, NumPy, Performance Tuning, Tensorflow, Standard Sql, Azure Machine Learning, Extensible Markup Language (XML), Enterprise Data Management, Enterprise Software Applications, Feature Engineering, Pytorch, Flask (Web Framework), Large Language Models, Prompt Engineering, Model Validation, Generative AI, Backend, Fastapi, Pandas, Scikit Learn, SAP S/4HANA, Machine Learning Operations, Data Lakehouse, Restful APIs, GPT - **Published:** June 13, 2026 - **Apply:** https://es.indeed.com/viewjob?jk=f3f9503d8f32d699 ## About the Role Do you have experience in XML?, * 5+ years of commercial experience in Data Science, Machine Learning, or Artificial Intelligence. * Strong programming skills in Python. * Hands-on experience with Pandas, NumPy, Scikit-learn, TensorFlow, and/or PyTorch. * Strong experience with Natural Language Processing and transformer-based architectures such as GPT, BERT, Llama, or similar models. * Experience with prompt engineering, fine-tuning, and implementation of Large Language Models. * Proven experience designing and implementing Retrieval-Augmented Generation (RAG) solutions. * Experience building and deploying machine learning models into production environments. * Strong understanding of supervised and unsupervised machine learning techniques. * Experience developing forecasting, classification, and predictive analytics models. * Solid knowledge of statistics, probability theory, experimentation, and model evaluation methodologies. * Experience working with SQL and/or NoSQL databases. * Familiarity with complex data formats such as JSON and XML. * Understanding of REST APIs and backend integration using frameworks such as Flask or FastAPI. * Ability to quickly understand complex domain-specific terminology and translate business requirements into scalable AI solutions. * Experience working within Agile or Sprint-based delivery environments. * Strong analytical thinking, problem-solving, and communication skills. * Upper-Intermediate or higher English level. Nice to Have * Experience with SAP S/4HANA or other ERP platforms. * Experience working with Data Lakehouse architectures and large-scale enterprise data environments. * Familiarity with specialized engineering data models or other specialized data structures. * Experience with graph databases or graph-based data modeling. * Knowledge of compliance automation, regulatory interpretation, or document intelligence solutions. * Experience in manufacturing, industrial, supply chain, engineering, or other highly regulated industries. * Exposure to MLOps practices and cloud-based AI/ML platforms. ## Description * Design, develop, and deploy production-grade machine learning and AI solutions. * Fine-tune and optimize Large Language Models (LLMs) for domain-specific use cases involving technical and regulatory documentation. * Build NLP pipelines capable of extracting structured rules and business logic from unstructured text sources. * Design and implement Retrieval-Augmented Generation (RAG) architectures for intelligent querying of large technical knowledge bases. * Develop time-series forecasting models for spend prediction, demand planning, and supply chain optimization. * Build machine learning models for supplier risk scoring, anomaly detection, and operational analytics. * Create scalable data extraction, transformation, and feature engineering pipelines from structured and unstructured data sources. * Collaborate with Data Engineers and Backend Engineers to integrate AI models into enterprise applications through RESTful APIs. * Optimize model performance, scalability, and reliability for large-scale processing workloads. * Validate model outputs, analyze model performance, and continuously improve prediction quality and accuracy. * Work closely with Product Managers, Domain Experts, and Engineering teams to ensure business requirements are translated into effective AI solutions. ## Related Videos - [Developer Experience, Platform Engineering and AI powered Apps](https://www.wearedevelopers.com/videos/990-developer-experience-platform-engineering-and-ai-powered-apps) - [Vectorize all the things! 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