ML Engineer

Equinix•Toronto, ON

5d•$88,000 - $132,000•Onsite

About The Position

Equinix is the world’s digital infrastructure company®, shortening the path to connectivity to enable the innovations that enrich our work, life and planet. A place where tech thinkers and future builders turn bold ideas into breakthrough experiences, we welcome your unique perspective. Help us challenge assumptions, uncover bias, and remove barriers—because progress starts with fresh ideas. You’ll find belonging, purpose, and a team that welcomes you—because when you feel valued, you’re empowered to do your best work. We are looking for an ML Engineer who can design, build, and integrate AI-powered systems by combining machine learning models, LLMs, APIs, and enterprise data into scalable, production-grade solutions. The role requires strong system thinking, the ability to translate business needs into technical architectures, and the capability to integrate model outputs into cohesive decision systems. Success in this role depends on close collaboration with Data Scientists, ML Engineers, and application teams to operationalize intelligent solutions.

Requirements

5+ years of experience in software engineering, AI/ML engineering, or related roles, with demonstrated experience in building and integrating production-grade systems
Bachelor’s degree in Computer Science, Machine Learning, Data Science, or a related field

Responsibilities

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 transfer and continuity
Take ownership of delivery by managing enhancements, releases, and system evolution
Stay current with industry trends and contribute to continuous improvement of team capabilities