Machine Learning Engineer, Senior (Madrid)

Machine Learning Engineer, Senior (Madrid)

13 sep
|
Grid Dynamics
|
Madrid

13 sep

Grid Dynamics

Madrid

We are looking for a talented Senior Machine Learning Engineer ¿Es usted el candidato adecuado para esta posibilidad? Asegúrese de leer la descripción completa a continuación.

- 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 xsgfvud ~ 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

📌 Machine Learning Engineer, Senior (Madrid)
🏢 Grid Dynamics
📍 Madrid

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