SPECIFICALLY, YOU WILL:

• Turn existing data science workflows into scalable, efficient production machine learning pipelines.
• Implement Feature Stores for managing and sharing features across multiple models.
• Establish and enforce best practices for CI/CD, version control, and automated testing within the ML lifecycle.
• Maintain our Neo4j instance, ensuring its performance, scalability, and security.
• Set up and maintain monitoring and alerting systems to ensure the health and performance of machine learning models and data pipelines.
• Integrate machine learning outputs seamlessly into relevant business systems, dashboards, and APIs.Document workflows, pipelines, and processes to ensure team members can reuse and maintain them.

The Senior ML Ops Developer builds and maintains the infrastructure powering Staples Canada’s machine learning initiatives. Translating data science models into scalable, reliable production solutions enables the business to fully leverage its data assets. Collaborating with data scientists and data engineers, you’ll streamline deployment and optimize model performance, ensuring seamless integration with business systems. This role drives efficiency and innovation through automation, improved model monitoring, and a robust machine learning ecosystem. You’ll also mentor team members, promoting MLOps best practices to positively impact the organization’s ability to derive value from machine learning and advance its data-driven culture.