Anuvaya

Member of Technical Staff - Applied AI Research

New Delhi, Delhi, IndiaFull timeStaffPosted 14 days ago
Apply on Anuvaya →

Sign into see who you know at Anuvaya.

ABOUT ANUVAYA

We think conversational AI agents will deliver all professional services in India. We started with astrology. We're a small group of engineers, designers, and product folks building at the intersection of conversational AI and domain expertise. Making an AI agent sound human-like is hard. Making an AI an expert in a domain is also hard. We're doing both together.

We're backed by Accel, Arkam Ventures, and Weekend Fund.

THE ROLE

Frontier models are incredible at English. They're not incredible at Indic languages and our users speak Hindi, Hinglish, Tamil, Telugu, and a dozen others. Our agent needs to be fluent, accurate, and domain-expert-level across all of them.

The Applied AI Research team owns two problems. First: finetuning models for our use case improving accuracy, fluency, and domain understanding in Indic languages where foundation models fall short. Second: making those models work reliably in production prompt engineering, context management, retrieval strategies, and the systems that turn a capable model into a domain expert.

You'll bridge the gap between research and production. Some weeks you're running finetuning experiments to improve Hindi response quality. Other weeks you're redesigning how context flows through a multi-turn conversation. The through-line is the same: make the model better at doing what our users need, in the language they think in.

WHAT YOU'LL DO

- Finetune models for Indic language performance improving fluency, accuracy, and domain understanding in Hindi, Hinglish, and other Indian languages

- Build and manage finetuning pipelines data curation, training runs, evaluation, and deployment of fine-tuned models

- Work with the team on prompt engineering and context management designing how the model receives and reasons over information across multi-turn conversations

- Design retrieval strategies that get the right domain data to the model at the right time

- Run experiments on model be...