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Hiring companySOAIS
Verified today
AI/ML Test Engineer
Bengaluru, Karnataka, India Full-time
About the role
SOAIS is a leading enterprise IT solutions provider offering technology solutions across Oracle Cloud Applications, PeopleSoft, WorkSoft, Workday, and niche areas such as mobility. The AI/ML Test Engineer designs and executes comprehensive test strategies to ensure the accuracy, reliability, performance, scalability, and robustness of AI/ML solutions. Day-to-day work includes designing test plans and cases, validating model outputs and performance metrics, testing data pipelines, and developing Python automation scripts. This full-time role is based in Bengaluru, Karnataka, India and is open to immediate joiners only.
What you’ll do
- Design and execute test strategies, test plans, test scenarios, and test cases for AI/ML applications
- Perform functional, integration, regression, system, API, and end-to-end testing
- Validate AI/ML model outputs against expected results and business requirements
- Test data quality, data pipelines, preprocessing, feature engineering, and data transformations
- Validate model performance using appropriate metrics such as accuracy, precision, recall, F1-score, ROC-AUC, MAE, and RMSE
- Identify and validate issues related to model bias, data drift, model degradation, and inconsistent predictions
- Perform testing of REST APIs and AI/ML services using tools such as Postman
- Develop and maintain automation test scripts using Python and frameworks such as PyTest
What you’ll bring
- Basic to good understanding of Machine Learning concepts and algorithms
- Understanding of supervised and unsupervised learning
- Experience validating ML model predictions and outputs
- Ability to design and execute test strategies, test plans, test scenarios, and test cases for AI/ML applications
- Proficiency in Python for developing and maintaining automation test scripts
- Familiarity with testing frameworks such as PyTest
- Ability to perform functional, integration, regression, system, API, and end-to-end testing
- Capability to validate model performance using metrics such as accuracy, precision, recall, F1-score, ROC-AUC, MAE, and RMSE
Skills
Machine Learning conceptsSupervised and unsupervised learningML model predictionsTest strategiesTest plansTest scenariosTest casesPython