Member of Technical Staff - Applied AI Research

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.