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 iden

📌 Language Alignment (India)
🏢 Meridial
📍 India