Data Annotation Specialist

We are looking for a meticulous Data Annotator to assist in preparing training and evaluation datasets for AI and machine learning projects catering to clients across the US, UK, and Europe. This role involves labeling text, documents, and images, as well as reviewing AI-generated responses while strictly following project-specific guidelines. Precision is critical since the effectiveness of AI models depends largely on the quality of the annotated data. The successful candidate will be responsible for verifying their own work, identifying ambiguous cases, and ensuring consistency within the team’s annotations.

Key Responsibilities
Label and tag various data types including text, documents, and images according to established project guidelines. Review AI-generated responses to assess accuracy, relevance, and tone, with tasks related to large language model (LLM) evaluation and reinforcement learning from human feedback (RLHF). Extract and organize information from documents such as invoices, forms, and reports. Conduct quality checks on both personal and team annotations, correcting errors as needed. Identify edge cases and unclear instructions, offering suggestions to improve annotation guidelines. Consistently meet daily targets for annotation volume and accuracy while maintaining up-to-date task tracking records.

Required Qualifications
1 to 3 years of experience in data annotation, data entry, content moderation, or other detail-oriented roles; fresh graduates are welcome to apply. A bachelor’s degree in any discipline is required. Strong reading comprehension and proficient written English skills are essential. Candidates must demonstrate high attention to detail and patience to perform repetitive, precise tasks. Comfortable working with Google Sheets or Excel and able to quickly learn new web-based tools. Ability to follow detailed written instructions accurately is a must.

Preferred Qualifications and Benefits
Experience with annotation tools such as Label Studio, CVAT, Labelbox, or Prodigy is advantageous. A basic understanding of how AI and machine learning models use labeled data is preferred. Exposure to LLM evaluation, prompt writing, or RLHF projects will be considered a plus.

Benefits include gym, travel, and food allowances, annual certification opportunities, paid time off and holidays, and bi-annual performance reviews with bonuses.

This position is based in Lahore and requires in-person attendance. Compensation starts at Rs50,000 per month. Applicants will be asked to provide their current gross salary and salary expectations in Pakistani Rupees during the application process.