Ml/Ai Engineer

? About the role We are looking for a Mid-Level ML/AI Engineer to join our team in Madrid.You will work at the intersection of machine learning, payment data, and cloud delivery, building AI-enabled systems that turn complex payment data into decisions our clients act on.At ARGOZ Consultants, we focus on delivering measurable impact on clients’ P&L, identifying and implementing optimization opportunities across scheme costs (Visa, Mastercard), interchange, and merchant pricing, often in the range of millions.You will help turn complex, granular payment data into reliable models, decision-support tools, and scalable production workflows.? Your role Design, build, and deploy the ML and AI systems behind our proprietary Saa S products.Build robust data and feature pipelines using payment-industry data.Own the production lifecycle of ML and data workloads: data ingestion, modelling, deployment, monitoring, and failure handling.Build and maintain the data layer: schemas, ingestion pipelines, and automated extraction from heterogeneous, often unstructured, external sources.Deploy and operate ML/data workloads in the cloud using Docker, Azure, Infrastructure as Code, and CI/CD practices.Apply LLM-based techniques-retrieval, structured extraction, and tool-using workflows-where they genuinely outperform simpler approaches, and demonstrate whether they do.Design rigorous evaluation workflows, including leakage-safe train/test splits, ranking metrics, error analysis, model calibration, comparison harnesses, and human expert validation.Work closely with senior payment, finance, and strategy stakeholders to translate complex business questions into sound technical solutions.Ensure that models are reproducible, observable, and usable by consultants and payment experts.? What we’re looking for At least 2 years of professional experience building and deploying ML, AI, or data-intensive systems.Strong Python skills, including the scientific stack (pandas, Num Py, scikit-learn) and at least one deep-learning framework (Py Torch preferred).Solid SQL skills and relational data-modelling experience.Hands-on cloud experience-Azure preferred; AWS or GCP equally valid-including containerization, CI/CD, and Infrastructure as Code.Practical experience with LLM-based systems: retrieval-augmented generation, embeddings, prompt and tool design, and evaluation.Fluency in English and Spanish.Comfort operating in ambiguity and tackling complex, unstructured problems.High ownership and accountability, with the ability to communicate technical results clearly to non-technical stakeholders.Valued, but not required: payments or fintech exposure; a formal quantitative background in physics, engineering, mathematics, or a related field.

? What we’re looking for At least 2 years of professional experience building and deploying ML, AI, or data-intensive systems. Strong Python skills, including the scientific stack (pandas, Num Py, scikit-learn) and at least one deep-learning framework (Py Torch preferred). Solid SQL skills and relational data-modelling experience. Hands-on cloud experience-Azure preferred; AWS or GCP equally valid-including containerization, CI/CD, and Infrastructure as Code. Practical experience with LLM-based systems: retrieval-augmented generation, embeddings, prompt and tool design, and evaluation. Fluency in English and Spanish. Comfort operating in ambiguity and tackling complex, unstructured problems. High ownership and accountability, with the ability to communicate technical results clearly to non-technical stakeholders. Valued, but not required: payments or fintech exposure; a formal quantitative background in physics, engineering, mathematics, or a related field.