We are seeking a Quality Test Engineer who will be responsible for designing and implementing test plans to validate the accuracy of extracted fields, verify OCR outputs, and ensure the seamless integration of the system into our data keying application. You will also work closely with ML Engineers and Software Developers to identify and resolve issues before deployment.

Responsibilities:

• Develop and execute test plans and test cases for the auto extraction tool.
• Validate field extraction accuracy from YOLOv9 models and OCR outputs.
• Perform functional, regression, and performance testing for ML and OCR components.
• Automate test cases for image preprocessing, model inference, and data extraction pipelines.
• Identify and document bugs, errors, and edge cases that impact extraction quality.
• Work closely with ML Engineers to fine-tune model outputs and improve precision.
• Collaborate with developers to ensure seamless integration and proper handling of extracted data.
• Monitor and analyze real-world errors, providing feedback to improve accuracy.
• Maintain detailed QA documentation and contribute to the continuous improvement of testing processes.

Qualifications:

• 3+ years of experience in software testing, preferably in ML/AI applications.
• Strong understanding of computer vision and OCR testing methodologies.
• Experience with test automation tools (Selenium, PyTest, or similar frameworks).
• Proficiency in Python for writing test scripts.
• Familiarity with Dockerized environments and testing within containers.
• Experience working with Azure cloud services is a plus.
• Ability to analyze model errors and suggest improvements in collaboration with ML Engineers.
• Strong analytical and problem-solving skills.
• Experience working in agile development environments.

Please refer to job description.