We are seeking a Senior Machine Learning Engineer to join our core technical team, bringing expertise in building production-grade ML systems, data engineering and managing the full lifecycle of machine learning models. This role will contribute to multiple initiatives ensuring impactful solutions for real business challenges.ResponsibilitiesDesign and develop machine learning models for forecasting, classification, recommendation, segmentation and optimizationPackage models for production and expose them via APIs or scheduled jobsImplement monitoring, retraining and lifecycle management for ML solutionsApply MLOps best practices, including model versioning, experiment tracking and reproducible pipelinesMonitor model performance in production and propose data-driven improvementsParticipate in technical design reviews and propose well-reasoned solutions with trade-offsDocument architectural decisions and facilitate knowledge transfer to internal teamsChampion engineering standards, tools and best practices across the teamCollaborate with business stakeholders to translate problems into machine learning solutionsRequirements3+ years of experience in ML Engineering or Data Engineering working with production systemsProven track record of delivering ML models actively used by real users with at least 2 live production projectsProficiency in Python, PySpark and SQLSkills in Scikit-learn, Databricks (production usage) and Delta LakeExpertise with REST APIs, Git, CI/CD pipelines, Docker and JenkinsKnowledge of MLflow for model versioning and experiment trackingBackground in time series forecasting, similarity techniques and computer vision modelsCompetency in feature engineering, model evaluation and monitoringStrong communication skills to collaborate effectively with non-technical stakeholdersAbility to balance model simplicity and complexity with sound judgmentEnglish proficiency at B2 level or higherNice to haveExperience in retail, fashion, consumer goods or distribution domainsFamiliarity with enterprise planning tools like SAP IBP, SAP M3 or SACBackground in building model monitoring dashboards with Power BI, Tableau or LookerKnowledge of semantic similarity or embeddings in product catalogsUnderstanding of multi-country or multi-currency platform challengesCapability to design Lakehouse architectures such as Medallion or Data Mesh#J-18808-Ljbffr