Senior Machine Learning Engineer
13 hours ago
Boadilla del Monte
ph3About Getnet /h3 /brpGetnet is the leading fintech provider of payment solutions in Latin America and Iberia . We offer robust, omnichannel solutions that cater to the unique needs of our customers, integrating seamlessly with existing ecosystems while delivering powerful proprietary capabilities. Our comprehensive suite of services includes payment gateway, in-store and e-commerce acquiring, processing, fraud prevention, financial services and value-added solutions tailored to industries such as retail, food beverage, health beauty, hospitality and travel. In 2025, Getnet processed over €238 billion across 10.5 billion transactions, serving 1.2 million clients. The company ranks as the largest acquirer in Latin America by number of transactions, and among the top 10 globally . Getnet operates across Brazil (as an e-commerce leader), Mexico, Chile, Argentina, Uruguay, Colombia, Spain, and Portugal. Getnet is built to serve merchants, ISVs, PayFacs, orchestrators, platforms and the next generation of commerce enablers, connecting technologies and markets through a unified, omnichannel payment experience that boosts performance and drives growth. /p /brh3Why join our team /h3 /brpIf you want to shape the future of financial solutions, this is the place! At Getnet, your work connects to something bigger, creating a real impact across global teams and markets for our clients and communities. Our people are our greatest strength. We combine growth opportunities, strong team connections, and a culture that supports your well-being and sense of belonging, so you can develop, contribute, and feel valued. With flexibility and autonomy built into how we work, you’ll have the space to focus, collaborate, and perform at your best. Here, your impact matters, your growth is supported, and your experience is designed to help you thrive. /p /brh3What you’ll do /h3 /brul /brliDesign, train and deploy scalable machine learning models using Getnet data to solve high-impact payment and business challenges across geographies. /li /brliBuild and maintain end-to-end machine learning pipelines, from exploration and feature engineering through scoring, deployment and monitoring. /li /brliLead the technical design and delivery of proofs of concept and new AI/ML initiatives within Getnet Payments' AI Lab. /li /brliDrive decisions on model architecture, experimentation and deployment, balancing performance, scalability, explainability and maintainability. /li /brliPartner with business, product and cross-functional teams to turn prioritized opportunities into production-ready data solutions. /li /brliStrengthen engineering quality through clean code, automated testing, documentation, version control, CI/CD and reusable standards. /li /brliMonitor production models for drift, data quality, performance and reliability, using alerts and dashboards to guide action. /li /brliMentor junior colleagues and communicate complex findings clearly to non-technical stakeholders across markets. /li /br /ul /brh3What we’re looking for /h3 /brpbProfessional Experience /b /p /brul /brli5+ years of professional experience in Machine Learning Engineering, Data Science or Applied Research roles. (Required) /li /brliProven experience building, deploying and operating end-to-end machine learning solutions on tabular data at scale in production cloud environments. (Required) /li /brliExperience leading technical decisions, proofs of concept or AI/ML initiatives and supporting junior team members. (Required) /li /brliExperience working in agile, cross-functional teams across multiple markets or geographies. (Required) /li /brliExperience in fintech, payments, banking or e-commerce. (Required) /li /brliEducation Bachelor's or Master's degree in Computer Science, Mathematics, Statistics, Physics, Engineering or a related quantitative field. (Required) /li /brliPhD in a related quantitative field. (Preferred) /li /br /ul /brpbLanguages /b /p /brul /brliEnglish, professional proficiency. (Required) /li /br /ul /brpbHard Skills /b /p /brul /brliPython and core data and machine learning libraries, including pandas, NumPy, scikit-learn, XGBoost or LightGBM, SciPy and statsmodels. (Required) /li /brliApplied 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) /li /brliObservational causal inference, uplift modeling, A/B testing and experimental design, including familiarity with EconML, causalml and DoWhy. (Required) /li /brliAzure 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) /li /brliTime-series and model-monitoring techniques, including change point detection, clustering, seasonality and trend analysis, drift detection, data quality alerts and performance dashboards. (Required) /li /brliTransformer and LLM concepts, prompt engineering and the integration and operationalization of LLM-based solutions through Azure OpenAI or similar services. (Required) /li /brliGit, CI/CD for machine learning, pytest, schema validation and clean, testable, well-documented Python code. (Required) /li /brliPreferred 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) /li /brliAWS services, including SageMaker, S3, Bedrock, EKS, Lambda, Step Functions and Glue, and experience working across Azure and AWS. (Preferred) /li /br /ul /brpbSoft Skills /b /p /brul /brliTechnical leadership, sound decision-making, ownership and accountability. (Required) /li /brliAnalytical thinking and structured problem-solving. (Required) /li /brliClear communication with technical and non-technical stakeholders. (Required) /li /brliCross-functional collaboration across markets and geographies. (Required) /li /brliAbility to mentor junior colleagues and foster continuous improvement. (Required) /li /brliPreferred Learning agility and curiosity about emerging AI technologies. (Preferred) /li /br /ul /brpGetnet is proud of being an organization where there are equal opportunities regardless of age, gender, disability, civil status, race, religion or sexual orientation. We are committed to providing an inclusive and accessible application process for all candidates. /p /brh3Our offer and benefits /h3 /brul /brliWe care for your well-being, so you will have health insurance, life insurance, dental insurance , annual health care, and access to Wellhub. /li /brliWe promote flexibility with a hybrid and collaborative model; the selected candidate must be ready to work 60% on-site. /li /brliWe aim to boost your growth with access to self-development programs. /li /brliWe aim to make your workdays more accessible, so you will have transportation allowance and meal voucher/food voucher. /li /br /ul /brpGetnet is part of Santander Group, one of the world’s leading financial groups, with a presence in more than 22 countries. /p /p #J-18808-Ljbffr