Databricks and AWS experts can shape MLOps at Fluent Media from Canada, focusing on reliable deployment, serving, scaling, and infrastructure efficiency. This senior engineer co-owns MLOps practices across Fluent Media’s data and machine learning team. You will operationalize models with ML scientists, Data Engineering, and Product while supporting accurate ad selection through dependable production systems. Python, SQL, PySpark, MLflow, and Delta Live Tables feature prominently.

Key Responsibilities
- Operationalize machine learning models in Databricks and AWS
- Build and optimize automated training, testing, and deployment pipelines
- Establish versioning, release control, testing, and monitoring standards
- Design scalable serving infrastructure for latency, reliability, and cost




- Track model performance, reliability, and infrastructure costs through dashboards

Requirements:
- Solid Databricks and AWS-based machine learning workflow experience
- Proficiency with Python, SQL, PySpark, and data engineering tools
- Experience with MLflow and Delta Live Tables
- Hands-on CI/CD, automated testing, and monitoring experience
- Architecture and operations ownership for low-latency relevance models Apply senior MLOps expertise across Databricks, AWS, model serving, automation, and production reliability at Fluent Media.

📌 Senior MLOps Engineer Databricks AWS (Toronto)
🏢 Fluent
📍 Toronto