Project Overview
We are sourcing independent Language Alignment & Resource Partners (LARPs) to provide native-level Marathi language vetting and QA for a specialized AI data project. As AI systems strive to reflect real-world usage and deliver human-like communication, their accuracy depends entirely on rigorous linguistic and cultural consultation. The objective of this project is to evaluate, annotate, and validate data to ensure high-quality outputs that are fully natural, polished, and free from bias.
Project Deliverables & Scope
Operate autonomously to provide linguistic QA and develop alignment resources. Expected deliverables include:
Data Annotation & Review: Reviewing, annotating, and testing AI outputs for grammatical accuracy, naturalness, and strict cultural context.
Quality Assurance & Vetting: Acting as a primary quality check during production to proactively identify and correct subtle cultural errors or awkward phrasing in the target language.
Resource Generation:



Analyzing task quality trends and autonomously developing educational resources and feedback documentation to increase alignment between AI task outputs and campaign expectations.
Production & Vetting Support: Providing native-level language vetting during project scaling and offering specialized linguistic consultation throughout the production phase.
Required Expertise
To successfully fulfill the deliverables of this project, Contractors must possess a meticulous eye for language and cultural nuance.
Core skillset includes:
Demonstrable work or educational experience in linguistics, education, or other fields requiring high attention to linguistic detail.
Prior, tangible experience working in human data evaluation or annotation.
Verified Marathi language proficiency of C1 or C2
The ability to confidently transform raw feedback and quality trends into structured, actionable educational resources.
A meticulous approach to language, with the sharpness to identify and correct even the most su

📌 Language Alignment (India)
🏢 Meridial
📍 India