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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Senior Machine Learning Engineer - **Company:** Grid Dynamics - **Location:** Cuenca, Spain - **Contract:** Permanent contract - **Skills:** Artificial Intelligence, Distributed Computing Environment, Python (Programming Language), Machine Learning, Tensorflow, Software Safety, Pytorch, Retrieval-Augmented Generation, Large Language Models, Multi-Agent Systems, Model Validation, Generative AI, Machine Learning Operations - **Published:** September 9, 2026 - **Apply:** https://www.buscojobs.com.es/senior-machine-learning-engineer-en-cuenca-ID-370156377 ## About the Role Strong understanding of machine learning fundamentals and model evaluation - Strong Python programming skills and experience with modern ML frameworks such as PyTorch, TensorFlow, or JAX - Understanding of retrieval-augmented generation (RAG), agentic systems, and LLM safety concepts - Experience training, fine-tuning, or adapting machine learning models - Experience working with Large Language Models beyond simple API integration - Experience evaluating AI systems and translating results into actionable recommendations - Experience building and maintaining machine learning systems and pipelines - Ability to work effectively in ambiguous problem spaces with incomplete requirements and limited data - Strong written and verbal communication skills Would be a plus: - Experience designing benchmarks, evaluation frameworks, or automated evaluation systems - Experience with distributed training or large-scale model inference - Experience building reusable ML tooling and internal platforms - Experience with cloud platforms and modern MLOps practices - Experience working on user-facing AI products at scale - Research experience or publications in machine learning or AI-related fields ## Description We are looking for a talented Senior Machine Learning Engineer - LLM Systems & Evaluation.This is an opportunity to work on next-generation AI systems, including large language models, retrieval-augmented generation, agents, and AI safety-focused evaluation.Essential functions: - Own machine learning projects from problem definition through implementation - Design and implement evaluation methodologies for AI and machine learning systems - Create datasets, benchmarks, and metrics to measure model and product performance - Evaluate and improve LLM-based systems, including RAG applications, agents, safety systems, and end-to-end AI products - Analyse model behaviour, identify failure modes, and recommend practical improvements - Build and maintain ML pipelines, tooling, and evaluation infrastructure - Collaborate with product, engineering, and research teams to translate business goals into measurable ML objectives - Prototype and iterate rapidly to solve business and product challenges - Communicate findings, trade-offs, and recommendations to both technical and non-technical stakeholders Qualifications: - 5+ years of experience in Machine Learning Engineering or a related field.- Strong understanding of machine learning fundamentals and model evaluation - Strong Python programming skills and experience with modern ML frameworks such as PyTorch, TensorFlow, or JAX - Understanding of retrieval-augmented generation (RAG), agentic systems, and LLM safety concepts - Experience training, fine-tuning, or adapting machine learning models - Experience working with Large Language Models beyond simple API integration - Experience evaluating AI systems and translating results into actionable recommendations - Experience building and maintaining machine learning systems and pipelines - Ability to work effectively in ambiguous problem spaces with incomplete requirements and limited data - Strong written and verbal communication skills Would be a plus: - Experience designing benchmarks, evaluation frameworks, or automated evaluation systems - Experience with distributed training or large-scale model inference - Experience building reusable ML tooling and internal platforms - Experience with cloud platforms and modern MLOps practices - Experience working on user-facing AI products at scale - Research experience or publications in machine learning or AI-related fields ## Related Videos - [Introduction to Azure Machine Learning](https://www.wearedevelopers.com/videos/368-introduction-to-azure-machine-learning) - [Your imaginations is (no longer) the limit: how Generative AI empowers people to be creative](https://www.wearedevelopers.com/videos/741-your-imaginations-is-no-longer-the-limit-how-generative-ai-empowers-people-to-be-creative) - [Machine learning in the browser with TensorFlowjs](https://www.wearedevelopers.com/videos/155-machine-learning-in-the-browser-with-tensorflowjs) - [Photonic Computing: Programming a New Class of AI Accelerators (incl. Live Coding)](https://www.wearedevelopers.com/videos/100196-photonic-computing-programming-a-new-class-of-ai-accelerators-incl-live-coding) - [AI Model Management Life Circles: ML Ops For Generative AI Models From Research to Deployment](https://www.wearedevelopers.com/videos/1152-ai-model-management-life-circles-ml-ops-for-generative-ai-models-from-research-to-deployment) - [Overview of Machine Learning in Python](https://www.wearedevelopers.com/videos/840-overview-of-machine-learning-in-python) ## Related Articles - [What Are Large Language Models?](https://www.wearedevelopers.com/magazine/304-what-are-large-language-models) - [Graph and AI Trends 2026: Why Is AI Running but Not Yet Delivering?](https://www.wearedevelopers.com/magazine/680-graph-and-ai-trends-2026-why-is-ai-running-but-not-yet-delivering) - [How to Become an AI Engineer](https://www.wearedevelopers.com/magazine/331-how-to-become-an-ai-engineer) - [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)