Lingala Bilingual Transcription Specialist

About OpenTrain

OpenTrain is the centralized platform for people who build careers in AI training and data labeling. We help contributors find projects, consolidate opportunities, and grow a unified portfolio of annotation work that supports state-of-the-art AI systems.

Work discovered through OpenTrain is entirely remote and often flexible, making it a strong option for part-time work, students, or people building freelance careers in an expanding industry that directly shapes how AI models behave.

About this role

This opening is for a Lingala bilingual transcription and language evaluation specialist working on video-based AI training tasks. The project—listed by OpenTrain—combines detailed transcription, timestamping, tone and intent capture, and linguistic analysis in Lingala and English.

The role is contract, part-time, and remote. Work supports model fine-tuning and evaluation by producing high-quality transcriptions and language ratings.

• Data type: Video
• Label types: Transcription and evaluation/rating
• Languages: Lingala (native or near-native) and English
• Estimated commitment: Less than 20 hours/week; reliable availability for at least 15 hours/week
• Employment: Contractor, part-time
• Pay: Hourly, typically between $45–$95 USD per hour (rates vary by task)
• Annotation software: Other (project will provide the interface)

What you'll do

You will produce high-quality linguistic deliverables that help train and evaluate language models. Tasks require careful listening, cultural sensitivity, and clear written explanations of nuance.

• Transcribe spoken Lingala in video content with accuracy and appropriate punctuation
• Add precise timestamps and identify speaker turns where applicable
• Describe emotional tone, speaker intent, and nonverbal cues relevant to meaning
• Evaluate grammar, tone, and overall language structure in Lingala and English content
• Define and explain conceptual meanings of words and phrases with cultural/contextual nuance
• Complete complex language tasks to support model training and fine-tuning while meeting quality standards

Requirements

Applicants must meet the core language and availability requirements below. All requirements come from the project brief and are required to be considered.

• Native or near-native proficiency in Lingala and English
• Strong written and verbal communication skills in both languages
• Excellent attention to detail for transcription and linguistic analysis
• Ability to identify and describe emotional nuance and tone in speech
• Experience in transcription, translation, localization, or other linguistics-focused work
• Reliable availability for at least 15 hours per week

Helpful background (preferred)

These qualifications are not strictly required but will strengthen your application and may lead to better-fit tasks or higher-paying assignments.

• Studies or experience in linguistics, language education, or related fields
• Prior involvement with AI, NLP, or data annotation projects
• Familiarity with high-quality transcription and annotation best practices

How the work is done

Work is performed remotely through the annotation interface provided by the project (software: OTHER). You will complete tasks independently, follow detailed guidelines, and submit annotations for quality review.

Expect iterative feedback: samples may be audited and you may receive guidance to align with project standards. Communication and collaboration are remote and asynchronous.

• Complete tasks using the provided annotation tool and style guides
• Follow project guidelines for timestamps, speaker labels, and tone descriptions
• Receive quality checks and revise work as requested to meet standards
• Paid per hour at the stated rate range; exact pay depends on task and qualification

Who should apply and next steps

This role is a great fit if you are fluent in Lingala and English, experienced or comfortable with detailed transcription work, and want flexible part-time remote work that contributes directly to AI development.

To apply, build your OpenTrain profile, confirm your language proficiency and availability, and submit your application. OpenTrain lets you track projects and grow a portfolio of annotation work over time.