AI Testing Engineer

An AI Testing Engineer is responsible for evaluating the accuracy, reliability, and performance of AI-based applications and systems. Key responsibilities include:

• Developing and executing test plans, test cases, and test scenarios for AI models.
• Implementing quality assurance standards to ensure AI solutions meet industry benchmarks.
• Designing benchmarking tests to evaluate AI system performance.
• Developing and maintaining automated test frameworks for AI component testing.
• Identifying and reporting defects, writing detailed bug reports, and verifying fixes.
• Analyzing AI model results to identify strengths, weaknesses, and areas for improvement.
• Ensuring ethical AI testing, including bias detection and fairness assessments.
• Collaborating with developers, data scientists, and project managers to refine AI models.

Required Skills:

• Proficiency in Python for image processing, data processing, and automation testing.
• Experience with machine learning frameworks such as TensorFlow, Keras, or PyTorch.
• Understanding of Software Development Life Cycle (SDLC) and Software Testing Life Cycle (STLC).
• Experience in API testing using tools like Postman.
• Familiarity with AI model monitoring tools such as Neptune, Weights & Biases, and TensorFlow Model Analysis.
• Strong statistical analysis skills for evaluating AI model performance.

Qualifications:

• Bachelor’s or Master’s degree in Computer Science, Data Science, Machine Learning, or related fields.
• 4+ years of experience in AI testing, deep learning, or quality assurance.
• Certifications such as ISTQB Certified Tester or ISTQB Certified AI Tester are preferred.