About the role
Who you are
- 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
- 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
What the job involves
- 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
- Success in this role depends on close collaboration with Data Scientists, ML Engineers, and application teams to operationalize intelligent solutions
- 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
Not the right fit? Search for Machine Learning Engineer jobs in Toronto
About Equinix
Internet Publishing
10,000+
Equinix (Nasdaq: EQIX) is the world’s digital infrastructure company™, enabling digital leaders to harness a trusted platform to bring together and interconnect the foundational infrastructure that powers their success. Equinix enables today’s businesses to access all the right places, partners and possibilities they need to accelerate advantage. With Equinix, they can scale with agility, speed the launch of digital services, deliver world-class experiences and multiply their value.
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About the role
Who you are
- 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
- 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
What the job involves
- 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
- Success in this role depends on close collaboration with Data Scientists, ML Engineers, and application teams to operationalize intelligent solutions
- 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
Not the right fit? Search for Machine Learning Engineer jobs in Toronto
About Equinix
Internet Publishing
10,000+
Equinix (Nasdaq: EQIX) is the world’s digital infrastructure company™, enabling digital leaders to harness a trusted platform to bring together and interconnect the foundational infrastructure that powers their success. Equinix enables today’s businesses to access all the right places, partners and possibilities they need to accelerate advantage. With Equinix, they can scale with agility, speed the launch of digital services, deliver world-class experiences and multiply their value.