Build dependable machine learning platforms for Fluent Media in Canada, using Python and PySpark to improve model operations and production reliability. As a Senior MLOps Engineer, you will establish engineering standards across the model lifecycle. The work spans automated pipelines, model versioning, release controls, performance monitoring, and low-latency serving endpoints. Collaboration includes ML scientists, engineers, and Product, with responsibility for resolving complex production challenges independently. Key Responsibilities:
Build pipelines for model training, testing,
and deployment Define automated testing and model release controls Investigate complex issues across the machine learning lifecycle Review designs and code while mentoring colleagues Document repeatable MLOps workflows and engineering practices Requirements:
Proficiency with Python, SQL, PySpark, and related tools Experience managing machine learning lifecycles with MLflow Proven ownership of real-time model serving architecture Ability to resolve production challenges independently Experience reviewing pull requests and mentoring colleagues Bring hands-on platform engineering, lifecycle management, technical leadership, and production troubleshooting skills to Fluent Media’s MLOps team.