Independently leads and holds responsibility for multifaceted programs made up of multiple projects and processes; develops and reviews business cases for change and improvement Design and build end-to-end AI systems integrating ML models, LLMs, APIs, and enterprise data Translate business requirements into scalable system architectures and solution designs Develop backend services and API-driven architectures to operationalize intelligent systems Implement data and model pipelines integrating structured and unstructured data sources Work closely with Data Scientists and ML Engineers to integrate model outputs into production systems and decision workflows Apply agent-based workflows and multi-step orchestration to enable complex system behavior Ensure systems are production-ready—scalable,



reliable, secure, and performant Continuously improve system performance through testing, monitoring, and iterative refinement Work closely with business, product, Data Science, and engineering teams to co-create solutions and align on outcomes Translate ambiguous problems into structured requirements and actionable system designs Engage stakeholders regularly to refine solutions and drive adoption Collaborate across teams to ensure integration with existing systems and enterprise standards Maintain high-quality documentation and enable knowledge

📌 Ai/Machine Learning Engineer (Toronto)
🏢 Equinix
📍 Toronto