We are looking for an experienced Machine Learning Architect to lead the design and implementation of scalable AI and ML solutions across modern cloud data platforms. This role combines architecture, engineering, and strategic leadership to enable enterprise‐scale machine learning capabilities. The ideal candidate has strong hands‐on experience with Databricks and a deep understanding of the ML lifecycle management, MLOps, scalable data architectures, and AI platform governance. This is a highly collaborative role working closely with Data Engineering, Data Science, Product, and Business stakeholders to design robust, scalable, and production‐ready AI solutions.ResponsibilitiesDefine and lead the architecture for scalable Machine Learning and AI platformsDesign end‐to‐end ML workflows using Databricks, including: Feature engineering, Model training, Experimentation, Deployment, MonitoringArchitect scalable data pipelines for AI/ML workloads using: Apache Spark, Python, SQLEstablish MLOps best practices including: CI/CD for ML, Model versioning, Model governance, Automated retraining, Model drifting, Observability and monitoringDesign secure and compliant AI architectures aligned with governance and privacy standardsPartner with Data Engineering teams to optimize data models and feature storesGuide Data Scientists and ML Engineers on scalable production design patternsEvaluate and integrate modern AI capabilities, including (this will be a plus): LLMs, Vector databases, Retrieval augmented generation (RAG), AI agentsDrive cost optimisation, scalability, and operational excellence across ML platformsDefine reference architectures and best practices across multiple ML teams (not just owning a single project)Support stakeholder engagement and translate business needs into scalable technical solutionsRequirements8+ years in Data, AI or Machine Learning Engineering roles3+ years designing ML platforms or AI architecture at scaleStrong hands‐on experience with:DatabricksApache SparkPythonSQLStrong understanding of:MLOpsML lifecycle managementDistributed ML systemsFeature engineeringModel deployment patternsDatabricks Unity Catalog, Delta Lake and Lakehouse architecture experienceExperience with cloud platforms (AWS, Azure, or GCP)Experience deploying ML models into production environmentsStrong knowledge of data architecture and scalable ETL/ELT patternsExperience working with orchestration frameworks such as Apache AirflowStrong stakeholder communication and technical leadership skillsBenefitsHealth InsuranceFlexible working hoursOpen holidays – take the time you need for yourselfProfit distribution for everyoneAnnual Mindera trip, sports and sharing groups to connect and have funTraining and conferences – create your own training planChild Care vouchersChoose laptop and peripherals that best suit your needsHotspot with unlimited usage for work or leisureSnack provisions at the officePartnerships with local businessesLocations: Porto, Aveiro, Coimbra, Portugal – remote options may be considered based on your location.#J-18808-Ljbffr