QA Lead - AI/ML

TechDigital Group; Bolingbrook (IL); On-site; USD 100,000 - 130,000; Full time

Job summary

A technology solutions provider is looking for an experienced AI/ML Test Lead located in Bolingbrook, Illinois. The role entails owning the quality assurance process for AI-driven solutions, defining and executing testing strategies while ensuring data accuracy and AI output quality. Candidates should possess extensive QA experience, particularly in AI/ML validation, and have a strong background in testing data-heavy systems. This position includes collaborating with various teams to ensure robust performance and compliance with standards.

Qualifications

• 10+ years of experience in QA / Testing roles, with leadership responsibility.
• Strong experience defining test strategy, test plans, and execution ownership.
• Experience testing data-heavy and analytics-driven systems.

Responsibilities

• Own end-to-end quality assurance for AI-driven solutions.
• Define and execute Enterprise AI testing strategy.
• Collaborate with Product Owners, AI Engineering Leads, and Data teams.

Skills

QA / Testing experience

AI/ML solution testing

Data validation

KPI testing

Job description

Overview

The AI/ML Test Lead will own end-to-end quality assurance for AI-driven solutions across Ulta's Enterprise AI. This role is responsible for defining and executing an Enterprise AI testing strategy, ensuring functional correctness, data accuracy, AI output quality, robustness, performance, and Responsible AI compliance. The role blends hands-on testing leadership, AI/ML-specific validation, and onsite stakeholder collaboration, working closely with Product Owners, AI Engineering Leads and Data teams.

Responsibilities

• 10+ years of experience in QA / Testing roles, with leadership responsibility
• Strong experience defining test strategy, test plans, and execution ownership
• Experience testing data-heavy and analytics-driven systems

AI / ML / Data Testing Skills

• Hands-on experience testing AI/ML or LLM-based solutions
• Strong understanding of:
• • Data validation and KPI testing
  • AI output correctness and consistency
  • Prompt-based and agent-based systems
• Familiarity with AI evaluation metrics (accuracy, error rate, hallucination rate, relevance)