QA Lead - AI/ML Testing

Acestack; Toronto; On-site; CAD 110,000 - 160,000; Full time

Job summary

Acestack is seeking a QA Lead for AI/ML Testing in Toronto, onsite. The role demands 10+ years in software testing and 3+ years directing AI/ML testing initiatives, guiding automated test strategies and governance across data, model, and security domains.

You will partner with data scientists, developers and product owners, driving QA maturity, defect management, and release readiness while mentoring the QA team and supporting agile delivery.

Qualifications

• 10+ years in Software Testing and QA.
• 3+ years leading AI/ML testing initiatives.
• Experience testing AI/ML, ML models, predictive analytics.
• Strong automation and defect management experience.
• Expert in Agile QA processes and governance.
• Excellent stakeholder communication and leadership.
• Experience mentoring QA teams.

Responsibilities

• Lead end-to-end test strategy, planning, execution, and quality governance for AI/ML solutions.
• Develop and implement testing frameworks covering functional, data, model, performance, security, and integration testing.
• Validate AI model accuracy, reliability, performance, and business outcomes.
• Collaborate closely with data scientists, developers, product owners, and business stakeholders.
• Drive test automation and continuous improvement of QA processes.
• Manage defect lifecycle, test reporting, release readiness, and quality metrics.
• Ensure AI/ML solutions comply with enterprise quality standards and AI governance requirements.
• Provide technical leadership, mentoring, and guidance to QA team members.
• Support Agile delivery teams throughout the software development and release lifecycle.

Skills

QA leadership

AI/ML testing

Test automation

Agile QA processes

Stakeholder management

Mentoring QA team

Model/data testing

Job description

Job Title: QA Lead - AI/ML Testing
Job Type: Full Time
Location: Toronto, ON (Onsite)

Job Description

We are seeking an experienced QA Lead - AI/ML Testing with 10+ years of overall experience in Software Testing and Quality Assurance, including 3+ years of hands-on experience leading AI/ML testing initiatives. The ideal candidate will have strong expertise in developing and executing comprehensive test strategies for AI, Machine Learning, Predictive Analytics, and Intelligent Automation solutions.

The QA Lead will be responsible for driving end-to-end testing activities, establishing quality standards, leading automation initiatives, and ensuring AI solutions meet functional, data, performance, security, and business requirements.

Key Responsibilities

• Lead end-to-end test strategy, planning, execution, and quality governance for AI/ML solutions
• Develop and implement testing frameworks covering functional, data, model, performance, security, and integration testing
• Validate AI model accuracy, reliability, performance, and business outcomes
• Collaborate closely with data scientists, developers, product owners, and business stakeholders
• Drive test automation and continuous improvement of QA processes
• Manage defect lifecycle, test reporting, release readiness, and quality metrics
• Ensure AI/ML solutions comply with enterprise quality standards and AI governance requirements
• Provide technical leadership, mentoring, and guidance to QA team members
• Support Agile delivery teams throughout the software development and release lifecycle

Required Skills & Experience

• 10+ years of experience in Software Testing and Quality Assurance
• 3+ years of experience leading AI/ML testing initiatives
• Strong experience testing AI, Machine Learning, Predictive Analytics, or Intelligent Automation solutions
• Experience with functional, data, model, performance, security, and integration testing
• Strong test automation and defect management experience
• Excellent understanding of Agile QA processes and quality governance
• Strong stakeholder management, communication, and leadership skills
• Experience mentoring and leading QA teams

Job Details

• Job Type: Full Time
• Location: Toronto, ON
• Work Model: Onsite