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AI QA Engineer
Job in
Alpharetta, Fulton County, Georgia, 30239, USA
Listed on 2026-02-19
Listing for:
Ova
Full Time
position Listed on 2026-02-19
Job specializations:
-
Software Development
AI Engineer, Machine Learning/ ML Engineer
Job Description & How to Apply Below
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 Responsibilities- Design, 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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