about 3 hours ago
Toronto, CanadaMid Level / Senior
Responsibilities
- Turn ambiguous business problems into clear system designs and implementation plans.
- Identify and implement opportunities to improve operational reliability and efficiency.
- Prototype and ship rapid experiments to test workflow improvements.
- Evaluate build-vs-integrate decisions for AI tools and automation.
- Build and maintain AI-powered automation and internal tools.
- Assess system architectures for scaling limitations and operational sustainability.
- Maintain clean, trustworthy data through thoughtful schemas and dashboards.
- Implement monitoring and alerting for model performance and drift detection.
- Troubleshoot production issues and conduct root cause analysis.
- Partner with data scientists to operationalize models.
- Develop runbooks, documentation, and best practices for AI Operations.
Requirements
- 5+ years of experience in operations and data.
- Familiarity with LLM deployment and context engineering.
- Comfortable writing SQL and working with APIs.
- Understanding of machine learning lifecycle concepts.
- Strong systems thinking and ability to evaluate global vs. local trade-offs.
- Excellent communication skills for both technical and non-technical audiences.
Benefits
- Opportunity to shape AI Operations from the ground up.
- Work on cutting-edge systems impacting customers and operations.
- Collaborate with talented engineers, data scientists, and product teams.
Tech Stack
DatabricksSnowflakeSQL
Categories
AI & MLData Engineering