Design scalable MLOps pipelines remotely from Canada, using Python, Apache Spark, and Databricks for machine learning workloads. Help productionize reliable data systems.
This MLOps / Data Engineer role bridges data science and production engineering for global digital audio advertising. You will build automated pipelines, optimize distributed processing, and deploy machine learning workflows. The work involves large-scale listener datasets, actionable audience intelligence, and cross-functional collaboration with data scientists and engineering teams.
Key Responsibilities
Build automated CI/CD pipelines for machine learning workflows
Develop distributed data pipelines with Apache Spark and PySpark
Configure Databricks and optimize cluster performance and costs
Deploy models through scalable APIs and batch systems
Implement testing, monitoring, and alerting mechanisms
Requirements
Professional Data Engineering, MLOps, or DevOps experience
Solid Python and Apache Spark programming skills
Advanced Databricks experience with Delta Lake
CI/CD experience with GitHub Actions or comparable tools
Residence in Ontario or Quebec, Canada
Apply MLOps, Python, Spark, and Databricks expertise to dependable audience intelligence infrastructure for digital advertising.