Recro.io - Quality Assurance Analyst - Regression/Performance Testing (7-8 yrs)

AI Quality Assurance Engineer.

About the Role :

Do you love building solutions and pioneering advancements in the AI technology space? a leader in travel technology, we're redefining the future of the travel industry through our experiential marketplace and SaaS platform.

We leverage the latest in digital transformation, data science, machine learning, and more, to create unique and personalized experiences driven by AI.

As an AI Quality Assurance Engineer, you will play a critical role in designing and implementing innovative AI solutions that meet the unique needs of our clients and ensure seamless adoption of our technology.

Responsibilities :

- AI System Testing.

- Develop and execute test plans and cases for AI/ML models, algorithms, and applications.

- Validate model outputs for accuracy, fairness, and reliability across use cases.

- Test AI system integration with enterprise platforms and applications.

Model Validation.

- Perform regression testing, Performance testing, stress testing, and scenario-based validation for models.

- Ensure models adhere to performance metrics (e.g, precision, recall, F1-score).

- Monitor and evaluate model drift and retraining requirements post-deployment.

Automation and Tools.

- Design and implement automated testing frameworks for AI systems.

- Leverage testing tools such as PyTest, Selenium, or specialized AI testing platforms.

Data Quality Assurance.

- Verify the integrity, accuracy, and consistency of training and testing datasets.

- Implement data validation frameworks to identify and rectify data quality issues.

Compliance and Ethics Testing.

- Audit AI systems for compliance with ethical guidelines and regulatory standards.

- Ensure adherence to fairness, bias mitigation, and explainability standards.

Documentation and Reporting.

- Maintain detailed documentation of test cases, results, and issue resolutions.

- Report QA metrics, such as defect density, test coverage, system performance and defect escape rate.

Qualifications :

- Experience with QA methodologies and tools such as JUnit, Postman, and PyTest, and proficiency in automation testing and CI/CD pipelines for AI systems.

- Knowledge of performance testing, model evaluation metrics, and experience with AI/ML models, data pipelines, and ML frameworks like TensorFlow, PyTorch, and Scikit-learn.

- Understanding of database technologies, including MongoDB, and big data tools such as Spark and Hadoop, with basic exposure to REST API testing.

- Ability to diagnose and resolve performance issues, with programming skills in Java, JavaScript, or similar languages being beneficial.

- Familiarity with ethical AI practices and regulatory compliance standards like GDPR and CCPA, and experience with cloud platforms such as GCP or AWS is preferred.