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.
Apply here: https://winnow.perle.ai/jobs/222cf812-620f-4346-9f55-87edc39efdf6
We are hiring expert Malay 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 Malay (Bahasa Melayu) as used in Malaysia, Brunei, and Singapore, with regional and ethnic variation. Project audio includes natural code-switching with English (Manglish) and lexical influence from Hokkien, Tamil, and other regional languages.
Primary speaker regions: Kuala Lumpur, Johor Bahru, Penang, Kota Kinabalu, Bandar Seri Begawan, Singapore.
Transcribe audio recordings into accurate, time-aligned written text following Perle's project-specific style guide
Apply correct conventions for speaker identification, overlapping speech, disfluencies, fillers, false starts, and non-speech events such as laughter, background noise, and music
Make principled orthographic decisions for dialectal, colloquial, and code-switched speech
Flag ambiguous segments, uncertain speakers, and audio quality issues using project conventions
Self-review every submission against Perle's quality bar before delivery
Engage with QA reviewers on edge cases, calibration sessions, and style guide updates
Native fluency in Malay with lifelong residence or deep immersion in Malaysia, Brunei, or Singapore
Mastery of Rumi (Latin) script orthography and awareness of Jawi where it appears
Ability to distinguish Malay from Indonesian in transcription decisions
Comfortable transcribing Manglish and other natural code-switching patterns
At least two years of professional transcription, captioning, court reporting, broadcast, translation, or linguistic annotation experience
Demonstrated accuracy at the word level under deadline pressure
Comfortable with web-based annotation platforms and variable-speed audio playback
Reliable high-speed internet, quality headphones, and a quiet workspace
Ability to commit to defined volume per week during active project phases
Background in Malay linguistics, translation, journalism, or education
Prior experience annotating Malay or Indonesian speech data
Working knowledge of Indonesian, Tamil, Mandarin, or Hokkien for cross-lingual audio
Familiarity with IPA or other phonetic transcription systems
Experience with verbatim versus clean-verbatim transcription conventions
Paid pilot task before full onboarding so both sides can calibrate
Per-task or per-minute compensation, with rates tied to audio complexity and turnaround
Flexible scheduling, with volume scaling up and down based on active client projects
Direct working relationship with Perle's linguistic leads and QA team
Eligible for invitation to additional Perle expert projects across related domains
Apply through Winnow, Perle's job portal at winnow.perle.ai. Find the role for your language under Open Jobs, set up your candidate profile, and complete the fully automated interview, which takes about 25 minutes. We review applications within 24 hours and invite passing candidates straight to the project.
Apply here: https://winnow.perle.ai/jobs/222cf812-620f-4346-9f55-87edc39efdf6
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.
Perle is an AI infrastructure company that builds expert-driven training data, evaluation systems, and applied AI products for leading AI labs and enterprises. The company specializes in creating high-quality linguistic and cultural data that requires genuine human expertise, including domain knowledge, linguistic nuance, and cultural fidelity that generic data vendors cannot provide. Their work powers speech recognition, dialogue systems, and evaluation frameworks for major AI partners including xAI, Samsung, ELM, and Unisys. Operating with experts across more than forty markets, Perle focuses on transcription, annotation, and data collection work that demands real human judgment and professional linguistic expertise rather than commoditized data entry.
