Machine Learning (ML)Technical Skills – Must have
Lead the design and development of AI-driven test automation frameworks and solutions.
Collaborate with stakeholders (e.g., product managers, developers, data scientists) to understand testing requirements and identify areas where AI automation can be effectively implemented.
Develop and implement test automation strategies for AI-based systems, encompassing various aspects like data generation, model testing, and performance evaluation.
Evaluate and select appropriate tools and technologies for AI test automation, including AI frameworks, testing tools, and automation platforms.
Define and implement best practices for AI test automation, covering areas like code standards, test case design, test data management, and ethical considerations.
Lead and mentor a team of test automation engineers in designing, developing, and executing AI test automation solutions.
Collaborate with development teams to ensure the testability of AI models and systems, providing guidance and feedback throughout the development lifecycle.
Analyze test results and identify areas for improvement in the AI automation process, continuously optimizing testing effectiveness and efficiency.
Stay up-to-date with the latest advancements and trends in AI and automation technologies, actively adapting and implementing new knowledge to enhance testing capabilities.
Knowledge in Generative AI and Conversational AI for implementation in test automation strategies is highly desirable.
Proficiency in programming languages commonly used in AI, such as Python, Java, or R.
Knowledge on AI frameworks and libraries, such as TensorFlow, PyTorch, or scikit-learn.
Familiarity with testing methodologies and practices, including Agile and DevOps.
Working experience on Python/Java and Selenium also knowledge in prompt engineering.
Shubham Vishwakarma
Full Stack Developer - Averlon
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Full Stack Developer - Averlon