Machine Learning Architect
M
MinderaAI / Engineering
BrazilFull-TimeSenior
Salary not disclosed
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Job Details
- Experience
- 8+ years in Data, AI, or Machine Learning Engineering roles; 3+ years designing ML platforms or AI architecture at scale.
- Required Skills
- PythonSQLApache AirflowCloud ComputingMachine LearningSparkDatabricksMLOps
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.
- Strong hands-on experience with Apache Spark, Python, and SQL.
- Strong understanding of MLOps and ML lifecycle management.
- Knowledge of distributed ML systems and feature engineering.
- Experience with Databricks Unity Catalog, Delta Lake, and Lakehouse architecture.
- 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.
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, and monitoring.
- Architect scalable data pipelines for AI/ML workloads using Apache Spark, Python, and SQL.
- Establish MLOps best practices including CI/CD for ML, model versioning, governance, automated retraining, and observability.
- 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 like LLMs, Vector databases, and RAG.
- Drive cost optimization, scalability, and operational excellence across ML platforms.
- Support stakeholder engagement and translate business needs into scalable technical solutions.
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