As AI companies push to make their models relevant across cultures and geographies, linguistic expertise has emerged as a critical skill in the AI economy.
AI is fuelling the rise of linguists who design prompts to test models on cultural nuance, bias, and taboos; benchmark responses for tone, accuracy, and cultural appropriateness; and review datasets to ensure they reflect diverse contexts. For Indian linguists, especially in underrepresented languages, opportunities are accelerating. Some US firms and recruitment platforms list rates ranging from $10 to $50 an hour, reflecting the growing demand and varied duration of projects.
Recruitment platform Talentmate, for instance, advertised for an in-country cultural and linguistic expert for India with idiomatic proficiency in Indian languages to train and evaluate AI models. The listing sought advanced degrees in sociolinguistics, anthropology, history, or cultural studies. Similarly, Madrid-based data labelling and annotation firm Sigma AI posted a remote opening for Telugu linguists. Demand is also growing at major tech firms. A Business Insider report noted that Meta is hiring contractors to work with locals in markets like India, Indonesia, and Mexico to develop characters for its AI-powered chatbots. The report said that the company is paying up to $55 an hour for workers fluent in Hindi, Indonesian, Spanish, and Portuguese, according to job descriptions reviewed by Business Insider. In India, Krutrim recently posted a role for a Kannada linguist in AI training and evaluation, involving dataset curation, language model assessment, and fine-tuning through Reinforcement Learning from Human Feedback (RLHF).Nishad Acharya, head of US AI startup Turing’s talent network, said the work is shifting from simple annotation to higher-order tasks like reasoning calibration, cultural safety review, and multimodal grounding. “Linguistic diversity is one of India’s greatest assets in the AI era. Languages like Kannada, Punjabi, and Bengali remain underrepresented in today’s models, but that’s quickly changing. Indian linguists are uniquely positioned to shape how AI serves more than a billion people. There’s enormous opportunity not just for language specialists but also for interdisciplinary talent who can fine-tune AI systems for healthcare, education, and finance,” he added. Suraj Amonkar, chief AI research & platforms officer at AI firm Fractal, echoed the sentiment, calling India’s linguistic diversity a core strength. “We believe Indian linguists are uniquely positioned to shape how AI understands and serves more than a billion people. This requires people who not only understand the language but also the local context to make AI more inclusive and impactful.” He also said newer models and algorithms have also made some of this process easier as we have seen some instances where the human annotation has moved from “labellers” to “verifiers.”Acharya noted that RLHF is most effective when feedback is nuanced and culturally grounded. “When fine-tuning multilingual models, we’ve observed significant gains in fluency and relevance when feedback comes from native speakers rather than translated datasets alone,” he said. Manish Gupta, senior director at Google DeepMind, highlighted efforts to strengthen Indic language AI. “We’ve been working with global teams on the next big leap in more effective Indian language models. Our Indic capabilities also power Gemma, Google’s family of powerful yet lightweight open models for developers, based on Gemini,” he said. Three startups selected by the India AI Mission—Sarvam, Soket AI, and Gnani—are building the next generation of ‘Make in India’ models on Gemma. Sarvam already built a 4B translation model to handle all 22 scheduled Indian languages, preserving context and cultural nuance. “We are also working on building multicultural understanding into our language models, to bridge the last mile between AI’s language capabilities and genuine cultural understanding,” Gupta added.
