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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Machine Learning Engineer - **Company:** Getnet - **Location:** Boadilla del Monte, Spain - **Contract:** Permanent contract - **Skills:** Clean Code Principles, Unity 3d, A/B Testing, Artificial Intelligence, Amazon Web Services, Amazon S3, Automation of Tests, Microsoft Azure, Continuous Integration, Data Systems, Monitoring of Systems, Apache Hive, Python (Programming Language), Machine Learning, NumPy, SciPy, Management of Software Versions, Feature Engineering, Large Language Models, Multi-Agent Systems, Prompt Engineering, Git, Pandas, Pytest, Data Lakes, Pyspark, Core Data, Scikit Learn, Information Technology, Statistics Packages, Xgboost, Machine Learning Operations, Software Version Control, Software Library, Key Vault, Databricks - **Published:** July 25, 2026 - **Apply:** https://www.jobleads.com/es/job/eeea3b6f473e5e77891dacbe9efe8b027 ## About the Role We are in search of a Senior Machine Learning Engineer to join our AI Lab in Boadilla del Monte, with the following qualifications and background: Professional Experience 5+ years of professional experience in Machine Learning Engineering, Data Science or Applied Research roles. (Required) Proven experience building, deploying and operating end-to-end machine learning solutions on tabular data at scale in production cloud environments. (Required) Experience leading technical decisions, proofs of concept or AI/ML initiatives and supporting junior team members. (Required) Experience working in agile, cross-functional teams across multiple markets or geographies. (Required) Experience in fintech, payments, banking or e-commerce. (Preferred) Education Bachelor's or Master's degree in Computer Science, Mathematics, Statistics, Physics, Engineering or a related quantitative field. (Required) PhD in a related quantitative field. (Preferred) Languages English, professional proficiency. (Required) Hard Skills Required Python and core data and machine learning libraries, including pandas, NumPy, scikit-learn, XGBoost or LightGBM, SciPy and statsmodels. (Required) Applied statistics, probability and linear algebra, with experience in classification, regression, uplift and anomaly detection at scale, feature engineering, temporal validation, explainability (XAI) and mathematical optimization. (Required) Observational causal inference, uplift modeling, A/B testing and experimental design, including familiarity with EconML, causalml and DoWhy. (Required) Azure Databricks, including Workflows, Delta Lake, Unity Catalog and Databricks Connect; Azure OpenAI Service, AKS and Key Vault; PySpark, Spark SQL and MLflow for tracking, registry, serving and versioning. (Required) Time-series and model-monitoring techniques, including change point detection, clustering, seasonality and trend analysis, drift detection, data quality alerts and performance dashboards. (Required) Transformer and LLM concepts, prompt engineering and the integration and operationalization of LLM-based solutions through Azure OpenAI or similar services. (Required) Git, CI/CD for machine learning, pytest, schema validation and clean, testable, well-documented Python code. (Required) Preferred LLM-based AI agents using LangChain, LangGraph, OpenAI Agents SDK, CrewAI or Agno, with knowledge of MCP, LangFuse, MLflow Tracing, multi-agent orchestration, RAG, tool use and domain-specific AI models. (Preferred) AWS services, including SageMaker, S3, Bedrock, EKS, Lambda, Step Functions and Glue, and experience working across Azure and AWS. (Preferred) Soft Skills Required Technical leadership, sound decision-making, ownership and accountability. (Required) Analytical thinking and structured problem-solving. (Required) Clear communication with technical and non-technical stakeholders. (Required) Cross-functional collaboration across markets and geographies. (Required) Ability to mentor junior colleagues and foster continuous improvement. (Required) Preferred Learning agility and curiosity about emerging AI technologies. (Preferred) ## Description As a Senior Machine Learning Engineer , these will be some of the key activities in your day-to-day role: Design, train and deploy scalable machine learning models using Getnet data to solve high-impact payment and business challenges across geographies. Build and maintain end-to-end machine learning pipelines, from exploration and feature engineering through scoring, deployment and monitoring. Lead the technical design and delivery of proofs of concept and new AI/ML initiatives within Getnet Payments' AI Lab. Drive decisions on model architecture, experimentation and deployment, balancing performance, scalability, explainability and maintainability. Partner with business, product and cross-functional teams to turn prioritized opportunities into production-ready data solutions. Strengthen engineering quality through clean code, automated testing, documentation, version control, CI/CD and reusable standards. 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