We are seeking a skilled and detail-oriented individual to join our team as a Data Annotation Specialist for a Generative AI project. In this role, you will be responsible for reviewing and labeling a diverse range of English text samples, including programming-related content, to identify whether each text is correct or incorrect. This project aims to train a state-of-the-art AI model to generate accurate and reliable text output.
Responsibilities:
1. Review and annotate a substantial volume of text samples (approximately 3000-5000 pieces) from a wide range of topics, including programming, technology, science, and various other subjects.
2. Carefully examine each text and make accurate judgments to classify them as correct or incorrect based on the provided guidelines.
3. Demonstrate good general knowledge and intelligence to evaluate the accuracy of the text independently.
4. Utilize effective web searching techniques to verify the correctness of ambiguous or unfamiliar content and ensure accurate labeling.
5. Collaborate with the project team to address any questions or concerns regarding the annotation guidelines or specific texts.
6. Maintain a high level of accuracy and consistency in the annotation process to ensure reliable training data for the AI model.
7. Provide feedback and suggestions to improve the annotation process and enhance the efficiency and quality of the project.
Requirements:
1. Strong command of the English language, both written and verbal, with excellent grammar and spelling skills.
2. Good general knowledge across a wide range of subjects, including programming and technology, enabling accurate assessment of the correctness of the text.
3. Attention to detail and ability to maintain focus while reviewing a large volume of text.
4. Proficient in conducting effective web searches to validate information
5. Familiarity with data annotation processes or working with AI projects is preferred but not required.
6. Bonus: Proficiency in (multiple, non-python) programming languages is a huge plus, though not mandatory.
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