AI QA Engineer
Listed on 2026-07-01
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Software Development
AI Engineer (Applied/Software), AI QA / Validation Engineer, Machine Learning/ ML Engineer
About The Role
We are looking for a highly skilled AI QA Engineer to join our team and ensure the quality, reliability, and performance of AI/ML-driven applications. The ideal candidate will have a strong background in software testing, a solid understanding of AI/ML workflows, and experience with automated testing frameworks. This role will focus on validating AI models, testing data pipelines, and ensuring the overall robustness of intelligent systems before deployment.
Key ResponsibilitiesDesign, develop, and execute test plans and test cases for AI/ML-based products.
Validate AI models for accuracy, fairness, robustness, and performance.
Test data pipelines, feature engineering processes, and model integration with production systems.
Develop automated test scripts for model APIs, training pipelines, and inference workflows.
Collaborate with data scientists, ML engineers, and software developers to identify and resolve quality issues.
Implement monitoring and alerting mechanisms for deployed AI systems.
Conduct regression testing to ensure changes do not degrade model performance.
Ensure compliance with data privacy, security, and responsible AI standards.
Bachelor's or Master's degree in Computer Science, Engineering, or related field.
3+ years of experience in software quality assurance, with at least 1 year in AI/ML testing.
Strong knowledge of QA methodologies, tools, and processes.
Hands-on experience with automated testing frameworks (e.g., PyTest, Selenium, Robot Framework).
Familiarity with ML frameworks (Tensor Flow, PyTorch, Scikit-learn).
Experience testing RESTful APIs and microservices.
Proficiency in Python (preferred), Java, or other programming languages.
Strong problem-solving skills and attention to detail.
Experience with ML model validation, monitoring, and drift detection.
Knowledge of MLOps tools (MLflow, Kubeflow, Airflow, CI/CD for ML).
Understanding of bias, fairness, and explainability in AI systems.
Exposure to cloud platforms (AWS, GCP, Azure) for AI/ML deployment.
ISTQB or equivalent certification in QA.
Competitive salary and benefits package.
Opportunity to work on cutting-edge AI products.
Collaborative, innovative, and growth-focused work environment.
Professional development and learning opportunities.
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