Machine learning SQA Testing

Description

1. Expertise in Agile Methodology

2. Strong experience in

   Agile

   methodologies, with a focus on continuous testing and delivery cycles.

3. Python Programming

4. Proficiency in

   Python

   (preferred) and

   Java

   for AI and ML automation tasks.

5. Testing AI & ML Models

6. Experience testing

   Generative AI

   models,

   Large Language Models (LLMs)

   , and AI-driven systems (e.g., Chatbots, AI agents).

7. Automation Frameworks for AI

8. Hands-on experience designing automation frameworks using tools like

   pytest

   ,

   mlflow

   ,

   Selenium

   , or

   Serenity BDD

   for AI/ML applications.
9. Estimation techniques for Automation testing efforts (Design and Execution).

10. Cloud Automation Strategy

11. Ability to develop automation test strategies for AI/ML applications deployed on

    public

    and

    private cloud environments

    .

12. API and Web Services Testing

13. Strong experience in testing

    RESTful APIs

    and

    Web services

    using tools like

    Postman

    and

    Rest API

    .

14. CI/CD Automation

15. Experience in testing and test planning for

    CI/CD

    solutions, especially for AI-driven products.

16. Test Management Tools

17. Proficient in using

    Azure DevOps (ADO)

    or other test management tools to streamline test case management and reporting.

18. Various Testing Types

19. Experience in

    Functional

    ,

    Regression

    ,

    UI/Usability

    , and

    Integration testing

    for AI/ML applications.

20. Exposure to Cloud Platforms

21. Good exposure to cloud platforms such as

    AWS

    and

    Azure

    for deploying and testing AI systems.

22. AI Product Workflow Understanding

23. Familiarity with agentic workflows and AI system interactions in end-to-end product use cases.