This role supports machine-learning development by reviewing and producing high-quality annotated datasets across multiple data types (text, images, video, audio, and other digital data). Working within defined annotation guidelines and quality-control processes, the role ensures accuracy, consistency, and timely completion of assignments while escalating ambiguous or sensitive cases and maintaining strict compliance with privacy and security requirements.
Responsibilities
- Review assigned data for machine-learning training, validation, and evaluation.
- Apply annotation guidelines to text, images, video, audio, or other digital data.
- Label, classify, categorize, transcribe, segment, or otherwise annotate data.
- Review existing annotations and correct errors or inconsistencies.
- Escalate ambiguous, sensitive, incomplete, or conflicting data.
- Apply detailed instructions accurately and consistently.
- Use annotation tools, spreadsheets, and collaboration platforms effectively.
- Communicate questions clearly and participate in calibration activities.
Required Qualifications
- Senior high school diploma, vocational qualification, or bachelor’s degree in a relevant field.
- Strong reading comprehension, written communication, reliability, and ability to meet deadlines.
- Commitment to confidentiality, privacy, security, and responsible data handling.
Preferred Qualifications
- Experience in data annotation, data labeling, content review, quality assurance, transcription, or research assistance.
- Experience reviewing text, images, video, audio, or other multimodal datasets.
- Familiarity with artificial intelligence, machine learning, natural language processing, or computer vision.
- Strong Filipino and English proficiency, including grammar, context, tone, idiomatic expressions, and culturally specific references, when required.
PH
