Junior QA Tester & AI Labeler

Job Description: As a Junior QA Tester & AI Labeler, you will be responsible for performing both software quality testing and AI data labelling tasks. Your role will be pivotal in ensuring that our applications are free of bugs and meet quality standards, while also preparing and annotating data for training machine learning models. You will work closely with developers, AI/ML engineers, and project managers to ensure the best quality and performance of our products. Software Testing: · Design, develop, and execute comprehensive test plans and test cases based on software requirements and technical specifications. · Perform manual and automated testing to ensure the quality, functionality, and usability of applications across different platforms and environments. · Identify, document, and track software defects or issues using bug-tracking tools (e.g., Jira, Bugzilla). · Work closely with developers to reproduce and resolve bugs and inconsistencies. · Perform regression testing to ensure new code changes do not break existing features. · Conduct performance, load, and stress testing to assess software stability. · Participate in sprint planning, daily stand-ups, and other Agile ceremonies as part of a collaborative team. AI Data Labelling: · Annotate and label large datasets (such as images, text, or videos) to provide accurate data for training machine learning models. · Follow specific labelling guidelines to ensure consistency and accuracy across the dataset. · Perform quality control on labelled data, ensuring it meets the standards set by data scientists and AI engineers. · Collaborate with data scientists to understand labelling requirements and adjust processes accordingly. · Clean and preprocess data to ensure it is in the appropriate format for machine learning applications. · Use AI labelling tools (e.g., Labelbox, RectLabel, Amazon SageMaker) for efficient data annotation and organization. Qualification & Experience: · Bachelor’s degree in computer science, Information Technology or a related study. · At least 1 year of experience software testing and with experience in AI data labelling. · Familiarity with version control systems (e.g., Git). · Strong attention to detail and ability to identify issues in both software performance and data quality. · Experience with data labeling tools and AI-related data processing (e.g., image/video/text annotation). · Familiarity with Agile development methodologies (e.g., Scrum, Kanban). · Ability to work with cross-functional teams, including software engineers and AI/ML engineers. · Excellent communication skills to document and report issues effectively. · Strong problem-solving skills and ability to work independently with minimal supervision.