Machine Learning Architect

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. This role has the responsabilities to: * + 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 (this will be a plus): 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. **Requirements** * + - 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.