AI Quality Engineer

Job Title: AI Quality Engineer

Location: Frankfurt Germany (Hybrid)

Type: Permanent OR Contract

Must be fluent German and English Speaker

Key responsibilities:

• Test Planning: Creating test plans and strategies for evaluating AI systems, including defining test objectives, selecting suitable testing methods, and identifying test scenarios.
• Test Execution: Performing various types of tests, such as functional testing, regression testing, performance testing, and usability testing, to evaluate the behavior and performance of AI algorithms and models.
• Defect Identification: Identifying and documenting defects, irregularities, or inconsistencies in AI systems and working closely with developers to rectify and resolve them.
• Data Quality Assurance: Ensuring the quality, consistency, and relevance of data used for training and testing AI models, which involves tasks like collecting, cleaning, preprocessing, and validating data. Identifying and mitigating bias in datasets.
• Test Data Generation: Generate synthetic data for variety, data for edge cases and input fuzzing
• Model Evaluation & Metrics: Understanding when to use which metric (Accuracy, Precision, Recall, F1-score), visualizing model performance (ROC Curves, Confusion Matrices), diagnosing & addressing Overfitting/Underfitting.
• Ethical and Bias Testing: Assessing AI systems for ethical considerations and potential biases to make sure they follow ethical standards and encourage inclusivity and diversity.
• Test Automation: Develop and maintain automated test scripts and frameworks for efficient and effective testing.
• Collaboration: Collaborating with diverse teams, including developers, data scientists, and domain experts, to understand requirements, validate assumptions, and align testing efforts with project goals.
• Documentation and Reporting: Documenting test methods, results, and suggestions in clear and brief reports for stakeholders.
• Drive continuous improvement and best practices in testing methodologies and processes for AI implementations.

Qualification requirement:

• 7+ years of experience in software testing, with a focus on AI or machine learning applications.
• Strong understanding of testing methodologies, techniques, and tools.
• Experience in designing and executing test cases for complex software systems.
• Proficiency in programming languages such as Python for test automation.
• Fundamental knowledge of AI, including ML, deep learning, NLP, and computer vision.
• Familiar with AI-driven testing tools and frameworks utilized for automating tests, predictive analytics, and generating intelligent test cases.
• Specialize in particular areas of AI testing, such as NLP testing, computer vision testing, or AI-driven test automation.
• Proficiency in testing AI-powered applications and systems, including chatbots, recommendation engines, and image recognition systems.
• Strong communication and collaboration skills.
• Transformation Experience in the CRM domain is good to have