GenAI Quality Engineer

Job Description:

Experience Desired: 10+ Years.

Qualification:

         The Generative AI Quality Engineer will play a crucial role in ensuring the quality and reliability of our AI models, and key feature delivery.. This position involves developing and executing testing strategies, designing test cases, and automating testing processes to ensure that our generative AI products meet the highest standards of performance and functionality.

Responsibilities:

• Develop and implement comprehensive testing strategies for generative AI models and systems.
• Design and execute test cases to evaluate the accuracy, performance, and reliability of AI models.
• Automate testing processes to streamline quality assurance workflows and improve efficiency.
• Collaborate with data scientists, AI researchers, and software engineers to understand model functionality and identify testing requirements.
• Monitor and analyze test results, identify defects and issues, and work with the development team to resolve them.
• Conduct performance testing to ensure AI models operate efficiently under various conditions and workloads.
• Stay updated with the latest advancements in AI and testing methodologies to continuously improve testing practices.
• Provide detailed documentation of testing processes, methodologies, and results.
• Ensure compliance with industry standards and best practices for AI quality assurance.

Qualifications:

• Bachelor’s or Master’s degree in Computer Science, Software Engineering, or a related field.
• Proven experience in quality assurance and testing, preferably with a focus on AI and machine learning models.
• Strong understanding of AI/ML concepts, particularly generative AI technologies.
• Proficiency in programming languages such as Python, Java, or similar.
• Experience with AI/ML frameworks and libraries (e.g., TensorFlow, PyTorch, scikit-learn).
• Familiarity with automated testing tools and frameworks (e.g., Selenium, JUnit, PyTest).
• Strong analytical and problem-solving skills with a keen attention to detail.
• Excellent communication and collaboration skills to work effectively with cross-functional teams.
• Ability to work in a fast-paced, dynamic environment and adapt to changing priorities.

Preferred Qualifications:

• Experience with natural language processing (NLP) and computer vision applications.
• Knowledge of cloud platforms and services (e.g., AWS, Azure, Google Cloud) related to AI development and deployment.
• Familiarity with DevOps practices and tools for CI/CD in the context of AI/ML projects.
• Understanding of data privacy and ethical considerations in AI development and testing