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Perle Systems is seeking expert Urdu transcribers to convert native-speaker audio into precise, time-aligned transcripts following a project style guide. You will decide on speaker labeling, overlap, and non-speech events with careful orthographic choices for dialects and code-switching.
Ideal candidates are native Urdu speakers with at least two years of transcription experience, strong Nastaliq literacy, and comfortable using web-based annotation tools.
Perle is an AI infrastructure company building expert-driven training data, evaluation systems, and applied AI products for the world's leading labs and enterprises. Our partners include xAI, Samsung, ELM, and Unisys. Headquartered in San Francisco with experts across more than forty markets, we specialize in the work that requires real human judgment: domain expertise, linguistic nuance, and cultural fidelity that generic data vendors cannot deliver.
We are hiring expert Urdu transcribers to convert audio recordings of native speakers into precise, conventionally formatted written transcripts. The work powers speech recognition, dialogue, and evaluation systems for major AI labs. Audio ranges from clean studio recordings to natural conversational speech in real-world acoustic conditions. You will be working at the level of expert linguistic judgment. This is not data entry. Decisions about orthography, code-switching, speaker attribution, disfluencies, and non-speech events shape the quality of every model trained on your output.
Standard Urdu as spoken in Pakistan and India, with natural Urdu-English code-switching common in urban speech. Project audio captures formal registers, conversational Urdu, and regional variation across the major Urdu-speaking centers. Primary speaker regions: Karachi, Lahore, Islamabad, Hyderabad, Lucknow, Delhi.
Perle hires experts on the basis of skill, language proficiency, and demonstrated quality. We welcome applicants from every background and every region where our target languages are spoken.
Originally posted on Himalayas