
ML SQA Testing Associate
4 days ago
- Expertise in Agile Methodology- Strong experience in Agile methodologies, with a focus on continuous testing and delivery cycles.
- Python Programming- Proficiency in Python (preferred) and Java for AI and ML automation tasks.
- Testing AI & ML Models- Experience testing Generative AI models, Large Language Models (LLMs), and AI-driven systems (e.g., Chatbots, AI agents).
- Automation Frameworks for AI- Hands-on experience designing automation frameworks using tools like pytest, mlflow, Selenium, or Serenity BDD for AI/ML applications.
- Estimation techniques for Automation testing efforts (Design and Execution).
- Cloud Automation StrategyAbility to develop automation test strategies for AI/ML applications deployed on public and private cloud environments.
- API and Web Services Testing-Strong experience in testing RESTful APIs and Web services using tools like Postman and Rest API.
- CI/CD Automation-Experience in testing and test planning for CI/CD solutions, especially for AI-driven products.
- Test Management Tools- Proficient in using Azure DevOps (ADO) or other test management tools to streamline test case management and reporting.
- Various Testing Types- Experience in Functional, Regression, UI/Usability, and Integration testing for AI/ML applications.
- Exposure to Cloud Platforms- Good exposure to cloud platforms such as AWS and Azure for deploying and testing AI systems.
- AI Product Workflow Understanding- Familiarity with agentic workflows and AI system interactions in end-to-end product use cases.
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