Job Overview
Job description
- Location:
- Remote (Indonesia)
- Work arrangement:
- Remote
Role Summary
About Perle
Perle powers the most ambitious AI initiatives in the world with human intelligence at scale. We work with the world’s leading model builders and enterprises to deliver expert-in-the-loop data, model evaluation, and trust systems that make AI safe, responsible, efficient and exceptionally high-performing.
Our clients don’t buy software, they buy outcomes: accuracy, reliability, and defensibility.
We’re an early-stage, founder-led company operating in the highest-stakes markets of AI. Every hire defines how we win.
- We are seeking a highly skilled and detail-oriented Native Bahasa Indonesia Speaker to evaluate and improve the quality of linguistic data, specifically in text and audio formats, for an AI/Natural Language Processing (NLP) project with perle.ai.
Responsibilities
- Data Annotation & Evaluation: Accurately evaluate and annotate large volumes of text and audio data in Bahasa Indonesia for linguistic quality, accuracy, clarity, and cultural appropriateness.
- Error Identification: Identify and categorize grammatical errors, syntactic issues, semantic inconsistencies, transcription errors, and inappropriate or non-native phrasing.
- Quality Assurance: Ensure the linguistic data adheres to project-specific guidelines and high-quality standards.
- Feedback & Reporting: Document and report linguistic issues and trends, providing clear, constructive feedback to improve the overall language model performance.
Requirements
- Native Speaker & Residency: Must be a native speaker of Bahasa Indonesia and currently residing in Indonesia.
- Education: Bachelor's Degree (minimum) from an accredited institution.
- Linguistic Background (Preferred): A degree in Linguistics, Indonesian Language and Literature (Sastra Indonesia), Translation, or a related field is highly preferred.
- Role:
- Bahasa Indonesia Language Specialist JD
- Job Type:
- Salaried, Full-Time
Company profile

Perle
perle.aiPerle is a company that brings expert human knowledge into AI, drawing on fifteen thousand doctors, lawyers, linguists, engineers and scientists across seventy countries. It runs training data, evaluation and labeling programs end-to-end through expert teams and a unified platform, helps teams scale with vetted specialists assessed through interviews and domain rubrics, and supplies continuously refreshed, expert-labeled multimodal and embodied data. Perle also offers red-teaming, refusal calibration and bias auditing led by domain experts, and publishes benchmarks on how frontier models handle tasks such as Arabic dialects.