QA Engineering Manager (AI/ML)

TL;DR

QA Engineering Manager (AI/ML): Leading a team of QA engineers in the design, development, and delivery of high-performance analytics and vehicle event analysis engines with an accent on computer vision, machine learning, and sensor fusion. Focus on architecting enterprise-scale testing frameworks and implementing CI/CD procedures for high-throughput systems.

Location: Madrid, Spain

Company

hirify.global is a global leader in data and software services that transforms the vehicle lifecycle into a connected digital experience through cognitive insights and automation.

What you will do

• Lead a team of QA engineers to deliver high-performance analytics engines for computer vision and ML.
• Design and implement procedures for process control, testing, and CI/CD.
• Establish and monitor metrics to ensure system effectiveness and high product quality.
• Oversee the development of manual and automated test frameworks and applications.
• Collaborate with development teams to identify and execute optimal test cases and automation strategies.
• Attract, mentor, and retain a high-performing quality assurance team aligned with business strategies.

Requirements

• BS/MS in Computer Science, Computer Engineering, or a related technical degree.
• 10+ years of experience in QA with at least 1 year in a professional management role within an agile environment.
• Proven track record in leading the architecture and operations of enterprise-scale testing frameworks.
• Experience with AI/ML-driven testing platforms and predictive analytics.
• Proficiency in Selenium, TestNG, and various API and load testing tools.
• Experience with the Scaled Agile Framework (SAFe) and Test Driven Development (TDD).

Culture & Benefits

• Innovative and fast-paced environment focused on cognitive answers and automation.
• Cultivates a culture of empathy, coaching, and professional growth.
• Strong commitment to continuous improvement and systematic reduction of technical debt.
• Collaborative and flexible mindset focused on pragmatic solution design.
• Opportunity to work with global-scale data processing and high-throughput systems.