Ai Qa Analyst

Your Mission
As an AI QA Analyst, you will:
Ensure the quality and reliability of AI-powered applications and machine learning models.
Design testing strategies adapted to AI systems and their specific challenges.
Validate model behavior, predictions, and business outcomes.
Improve testing processes and quality standards for AI-driven products.
Act as a quality advocate, helping teams deliver secure, accurate, and trustworthy AI solutions.
Key Responsibilities
Quality Assurance & Testing
Define and execute testing strategies tailored to AI/ML-based systems.
Design, maintain, and execute manual, exploratory, functional, and non-functional test scenarios.
Analyze user stories and business requirements to assess testing scope and feasibility.
Estimate testing effort and identify risks associated with AI models, data quality, and business rules.
Support User Acceptance Testing (UAT) activities and ensure business expectations are correctly reflected in delivered solutions.
Review test results and assess impacts on functionality, performance, and AI model behavior.
Identify, document, track, and validate defects through to resolution.
Produce clear test execution reports, quality assessments, and status updates.
AI & Machine Learning Testing
Validate AI model outputs for:Accuracy
Correctness
Robustness
Fairness
Explainability
Test model behavior across edge cases and unexpected scenarios.
Design and execute data validation and data quality testing procedures.
Validate data pipelines and input/output consistency.
Challenge requirements, acceptance criteria, and AI assumptions to ensure measurable business value.
Contribute to defining AI quality KPIs and success metrics, including:Accuracy
Precision
Recall
Model Performance Indicators
Collaboration & Continuous Improvement
Participate actively in Agile Scrum ceremonies and delivery processes.
Work closely with Product Owners, Developers, Data Scientists, and Business stakeholders.
Share knowledge and mentor junior QA professionals when needed.
Continuously improve testing methodologies, quality frameworks, and AI validation approaches.
Stay up to date with emerging trends in Artificial Intelligence, Machine Learning, and Quality Engineering.
✅ What We're Looking For
Mandatory Requirements
Minimum3 years of experience as a QA Analyst.
Hands-on exposure to AI/ML concepts and environments.
Understanding of:Supervised Learning
Unsupervised Learning
Model Training
Model Inference
Datasets and Data Quality
Experience designing and executing test strategies.
Strong analytical and problem-solving skills.
Experience working in Agile Scrum environments.
Strong communication and documentation skills.
Autonomous, proactive, and detail-oriented mindset.
Experience using:Jira
Xray
Professional level of English.
? Technical Skills
Quality Assurance
Functional Testing
Exploratory Testing
Regression Testing
User Acceptance Testing
Defect Management
Test Planning & Reporting
Risk-Based Testing
AI & Data Testing
AI Model Validation
Data Quality Testing
Data Pipeline Validation
AI Performance Assessment
Quality Metrics & KPIs
Bias & Fairness Testing
Explainability Validation
Data & APIs
SQL
Data Validation
Data Analysis
REST APIs
Postman
SoapUI
Test Automation
Knowledge of automation tools and frameworks such as:
Playwright
Selenium
Katalon
Scripting & Test Data
Python
Test Data Preparation
Automation Scripting
⭐ Nice to Have
Experience testing AI-powered applications or Machine Learning products.
Knowledge of model monitoring and AI governance principles.
Experience with automated testing frameworks.
Previous exposure to Data Science or Analytics environments.
French language skills.
Education
Degree in:Computer Science
Software Engineering
Data Science
Information Systems
Or a related field