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, Tensor

Flow, 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

📌 Senior Machine Learning Engineer (España)
🏢 Grid Dynamics
📍 España