Hindi Quality Coordinator – LLM Data & Model Training

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.