Hindi Quality Coordinator – LLM Data & Model Training

This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Hindi Quality Coordinator – LLM Data & Model Training based in India.

In this role, you will contribute to the development and improvement of advanced artificial intelligence systems by ensuring the quality, accuracy, and linguistic integrity of Hindi-language data used to train and evaluate Large Language Models (LLMs). You will support multilingual AI projects by coordinating language quality activities and ensuring that datasets meet established linguistic and project-specific standards. Working at the intersection of language expertise, data quality, and AI technology, you will help improve how AI models understand, interpret, and generate Hindi content. You will collaborate with linguists, data specialists, and project stakeholders to maintain consistent quality across training and evaluation workflows. This opportunity is ideal for a detail-oriented Hindi language professional interested in the rapidly evolving fields of artificial intelligence, natural language processing, and machine learning. You will contribute to impactful international projects within a collaborative, technology-driven, and remote working environment.

Accountabilities

• Coordinate Hindi language quality activities: Support the planning and execution of linguistic quality processes for AI training, data generation, and model evaluation projects.
• Ensure linguistic accuracy: Review Hindi-language content and datasets to assess grammar, spelling, vocabulary, fluency, cultural relevance, and overall linguistic consistency.
• Support LLM data preparation: Contribute to the validation, annotation, and refinement of Hindi-language datasets used for training and evaluating large language models.
• Monitor data quality: Identify linguistic inconsistencies, errors, ambiguities, and potential quality issues, ensuring that data meets established project guidelines and quality benchmarks.
• Coordinate quality workflows: Work with linguists, reviewers, data specialists, and project teams to organize quality assurance activities and maintain consistent delivery standards.
• Evaluate AI-generated content: Assess Hindi-language model outputs for accuracy, relevance, naturalness, contextual understanding, and alignment with linguistic and cultural expectations.
• Provide feedback and recommendations: Document recurring issues, communicate quality findings, and recommend improvements to annotation guidelines, review processes, and linguistic standards.
• Maintain project documentation: Ensure quality reports, review results, feedback records, and project-related documentation are accurate and up to date.
• Support continuous improvement: Identify opportunities to enhance linguistic evaluation methods, data quality processes, and overall model training effectiveness.
• Collaborate across teams: Coordinate with internal and external stakeholders to address quality concerns, resolve project challenges, and ensure alignment with delivery expectations.

Requirements

• Excellent written and spoken Hindi proficiency, with a strong understanding of grammar, syntax, vocabulary, semantics, and regional language variations.
• Strong English communication skills to collaborate effectively with international teams and understand project documentation and instructions.
• Experience in linguistic quality assurance, translation, proofreading, localization, language annotation, content review, or multilingual data projects.
• Understanding of AI, machine learning, natural language processing (NLP), or Large Language Model (LLM) concepts, with an interest in contributing to AI development.
• Familiarity with data annotation, linguistic evaluation, content validation, or quality assessment workflows.
• Strong attention to detail and the ability to identify linguistic inaccuracies, inconsistencies, contextual errors, and subtle differences in meaning.
• Excellent analytical and critical-thinking skills, particularly when evaluating language quality and AI-generated responses.
• Strong organizational and coordination abilities, with the capacity to manage multiple tasks, follow detailed guidelines, and meet project deadlines.
• Effective written and verbal communication skills, including the ability to provide clear, constructive feedback and document quality findings.
• Ability to work independently in a remote environment while collaborating effectively with cross-functional and international teams.
• Adaptability and willingness to learn new tools, technologies, and evolving AI data quality methodologies.

Additional Advantages

• Previous experience working on LLM training, AI evaluation, or generative AI data projects.
• Familiarity with annotation platforms, linguistic quality tools, and data management systems.
• Experience coordinating language teams, reviewers, or quality assurance workflows.
• Knowledge of Hindi dialects, regional expressions, cultural nuances, and contextual language usage.
• Academic background in Hindi, linguistics, translation studies, computational linguistics, or a related discipline.

Benefits

• Fully remote working arrangement, based in India.
• Opportunity to contribute to innovative multilingual AI and LLM development projects.
• Exposure to artificial intelligence, natural language processing, machine learning, and advanced language technologies.
• Opportunity to apply and develop Hindi linguistic expertise in a growing technology-driven industry.
• Collaboration with international teams and multilingual language professionals.
• Exposure to large-scale projects supporting global clients across diverse industries.
• Opportunities to develop expertise in AI data quality, linguistic evaluation, and model training.
• Dynamic and collaborative working environment focused on innovation, quality, and continuous improvement.

How Jobgether Works

We use an AI-powered matching process to ensure your application is reviewed quickly, objectively, and fairly against the role’s core requirements. Our system identifies the top-fitting candidates, and this shortlist is then shared directly with the hiring company. The final decision and next steps (interviews, assessments) are managed by their internal team.

We appreciate your interest and wish you the best!

Why Apply Through Jobgether?

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We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.

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