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Remote Generalist - English & Assamese - AI Trainer
Remote / Online - Candidates ideally in
New Bedford, Bristol County, Massachusetts, 02746, USA
Listed on 2026-06-03
New Bedford, Bristol County, Massachusetts, 02746, USA
Listing for:
Mercor
Remote/Work from Home
position Listed on 2026-06-03
Job specializations:
-
Social Work
Bilingual
Job Description & How to Apply Below
Position Overview
PLEASE NOTE:
You must take the Bilingual Competency interview in Assamese to be considered for this role.
Location:
Global | Type:
Contract Work | Fluent Language
Skills Required:
Assamese (native fluency) and English (strong proficiency)
Why this role matters:
Your job is to assess Assamese AI-generated responses and identify specific strengths and areas of improvement for these responses and your work will be used to create the "perfect AI-generated response" at a later stage of this project. Note the analysis you create will be in English.
- Conduct fact-checking using trusted public sources and external tools.
- Generate high-quality human evaluation data by identifying response strengths, areas for improvement, and factual inaccuracies.
- Assess reasoning quality, clarity, tone, and completeness of responses.
- Ensure model responses align with expected conversational behavior and system guidelines.
- You hold a Bachelor's degree.
- You are a native speaker in Assamese.
- You have significant experience using large language models (LLMs) and understand how and why people use them.
- You have excellent writing skills in English and can clearly articulate nuanced feedback.
- You have strong attention to detail and consistently notice subtle issues others may overlook.
- You have a background or experience in domains requiring structured analytical thinking (e.g., research, policy, analytics, linguistics, engineering).
- Prior experience with RLHF, model evaluation, or data annotation work.
- Experience writing or editing high-quality written content.
- Experience comparing multiple outputs and making fine-grained qualitative judgments.
- You identify factual inaccuracies, reasoning errors, and communication gaps in model responses.
- You produce clear, consistent, and reproducible evaluation artifacts.
- Your feedback leads to measurable improvements in response quality and user experience.
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