I build agentic systems, fine-tune LLMs, and get RAG working on real, messy data. Most of my time goes to the gap between a promising demo and something people can actually rely on.
I'm an AI Engineer at Otsuka Corporation in Tokyo, where I build and run production LLM systems — RAG chatbots on Elasticsearch, FAQ and quotation assistants with hybrid search and custom MCP tools, and fine-tuning pipelines across multi-node on-prem GPUs.
I studied at IIT Guwahati and work across the full ML lifecycle: data curation, training, RLHF, evaluation, and deployment. I like the unglamorous parts — reproducible baselines, honest evals, and pipelines that don't fall over. Living in Tokyo, JLPT N4 certified.
Open-source toolkits from my own work with language models.
A toolkit for poking around inside Mixture-of-Experts models and fine-tuning only the experts that matter. Finds the MoE layers (Mixtral, Qwen), watches which experts fire on your data, then trains just those with LoRA/QLoRA — far less compute, base model untouched.
view repository →Turns your domain text into training data. A small crew of agents — chunker, QA generator, validator, ORPO generator — runs in parallel to produce single- and multi-turn QA plus preference pairs, ready for fine-tuning or alignment.
view repository →❯ ls more/ → StockData_ETL, TextBoat, dev.connect · all repositories on GitHub →
I'm always happy to talk about AI engineering, research, or new opportunities — in English or Japanese. If you're building something interesting in ML or AI, drop me a line.