Archived listing. The details below describe a past opening.
Position: Senior AI/ML Test Lead
Location: Onsite- Toronto, ON
Job type: Full-Time/Permanent Hiring
As a Senior AI/ML Test Lead, you will lead end-to-end quality engineering and testing initiatives for AI, Machine Learning, Predictive Analytics, and Intelligent Automation solutions. The role combines strong QA leadership with specialized experience in AI/ML model validation, data testing, automation, performance, security, and integration testing.
Required Skills
- 10+ years of experience in Software Testing and Quality Assurance, including 3+ years leading AI/ML testing initiatives.
- Strong experience defining and executing end-to-end test strategies for AI/ML and analytics solutions.
- Experience testing AI models, Machine Learning solutions, Predictive Analytics, and Intelligent Automation.
- Strong understanding of functional, data, model, performance, security, and integration testing.
- Experience validating AI model accuracy, reliability, data quality, and business outcomes.
- Strong test automation and quality engineering experience.
- Experience with defect management, quality governance, and release readiness.
- Strong experience working in Agile delivery environments.
- Ability to collaborate with Data Scientists, Developers, Product Owners, and Business Stakeholders.
- Experience leading and mentoring QA/Test teams.
- Understanding of enterprise quality standards and AI governance requirements.
Roles & Responsibilities
- Lead end-to-end test strategy, planning, execution, and quality governance for AI/ML initiatives.
- Define and implement comprehensive testing frameworks covering functional, data, model, performance, security, and integration testing.
- Validate AI/ML model accuracy, reliability, data quality, and business outcomes in collaboration with Data Science and Engineering teams.
- Drive test automation and continuous improvement of AI/ML quality processes.
- Manage defects, risks, quality metrics, and release readiness across AI/ML solutions.
- Partner with Data Scientists, Developers, Product Owners, and Business Stakeholders to identify and address quality risks.
- Establish testing standards and ensure compliance with enterprise quality and AI governance requirements.
- Lead, coach, and mentor QA teams supporting AI/ML initiatives.
