AI Training Data Labeler & QA — Remote

prolificacademicltd; Stati Uniti; Remoto; USD 28.000 - 40.000; Tempo pieno

Descrizione del lavoro

prolificacademicltd is offering flexible remote work for individuals to contribute to AI data labeling through paid, task-based assignments. After a brief skills assessment, candidates may review and annotate data outputs, with assignments varying in length and some requiring an uninterrupted hour.

The role involves checking AI-generated data entries for accuracy, creating test data, and reporting quality issues according to guidelines.

Competenze

• Experience in high-volume data entry, data processing, database management, or records administration.
• Strong accuracy and attention to detail when working with large datasets, including spotting duplicates and inconsistencies.
• Ability to process structured and unstructured information efficiently without sacrificing quality.
• Understanding of data formats and validation rules, and ability to spot logical or factual problems in AI outputs.
• Written English skills sufficient to assess clarity and correctness.
• A PayPal account is required to receive task payments.

Mansioni

• Check AI-generated data entries, extracted information, and structured records for accuracy, completeness, and consistent formatting.
• Create realistic data-entry examples, including ambiguous or conflicting inputs, to assess how AI handles difficult cases.
• Identify categorization, labeling, and field-mapping errors in generated datasets and report them against quality guidelines.
• Label and classify samples to help teach models appropriate data structures and validation rules.
• Compare results with established data-entry standards and flag quality issues.

Conoscenze

High-volume data entry

Attention to detail

Structured and unstructured data

Data formats and validation rules

Written English

Strumenti

Excel

Google Sheets

Airtable

SQL

Access

Confluence

Notion

Descrizione del lavoro

prolificacademicltd is offering flexible remote work for individuals to contribute to AI data labeling through paid, task-based assignments. After a brief skills assessment, candidates may review and annotate data outputs, with assignments varying in length and some requiring an uninterrupted hour.

The role involves checking AI-generated data entries for accuracy, creating test data, and reporting quality issues according to guidelines.