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 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.Responsibilities- Define and lead the architecture for scalable Machine Learning and AI platforms.
- Design end-to-end ML workflows using Databricks, including Feature engineering, Model training, Experimentation, Deployment, Monitoring.
- Architect scalable data pipelines for AI/ML workloads using Apache Spark, Python, SQL.
- Establish MLOps best practices, including CI/CD for ML, model versioning, model governance, automated retraining, model drifting, observability and monitoring.
- Design secure and compliant AI architectures aligned with governance and privacy standards.
- Partner with Data Engineering teams to optimize data models and feature stores.
- Guide Data Scientists and ML Engineers on scalable production design patterns.
- Evaluate and integrate modern AI capabilities, including LLMs, Vector databases, Retrieval augmented generation (RAG), AI agents.
- Drive cost optimization, scalability, and operational excellence across ML platforms.
- Define 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 solutions.Qualifications- 8+ years in Data, AI, or Machine Learning Engineering roles.
- 3+ years designing ML platforms or AI architecture at scale.
- Strong hands-on experience with Databricks, Apache Spark, Python, SQL.
- Strong understanding of MLOps, ML lifecycle management, distributed ML systems, feature engineering, model deployment patterns.
- Databricks Unity Catalog, Delta Lake, and Lakehouse architecture experience.
- Experience with cloud platforms (AWS, Azure, or GCP).
- Experience deploying ML models into production environments.
- Strong knowledge of data architecture and scalable ETL/ELT patterns.
- Experience working with orchestration frameworks such as Apache Airflow.
- Strong stakeholder communication and technical leadership skills.The Things We Really Care About- Health Insurance, because health comes first.
- Flexible working hours.
- Open holidays, take the time you need for yourself.
- Profit distribution for everyone.
- Mindera Annual Trip, Sports, and sharing groups to connect and have fun.
- Training & conferences, create your own training plan.
- Child Care vouchers.Other Good Things- Choose Laptop & Peripherals that best suit your needs.
- Hotspot with unlimited usage for work or Netflix.
- We have amazing offices in Porto, Aveiro, and Coimbra if you want to physically connect with minders.
Remote from Portugal is also an option.
Remote from other Countries will depend on your current location and Projects.
- At the offices, we have a wide range of snacks to keep you fed and healthy.
- Partnerships with local businesses.
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