Research Engineer · IBM Research
I build training infrastructure and data pipelines for large language models at IBM Research. My work spans pretraining, post-training alignment, and agentic systems.
Notes on training large language models, from someone who builds the pipelines.
Research engineering work at IBM — pretraining, post-training, and agentic systems.
I'm a Research Engineer at IBM Research, where I build and train large reasoning models. My work spans pretraining, post-training alignment, and agentic systems.
Currently I'm building an agentic browser pipeline for RL rollout generation across multiple real-world environments (Gmail, Slack, Notion, etc.) — enabling trajectory generation at scale for RL training.
Previously I contributed to Bamba — a hybrid Mamba2-Attention architecture pretrained on ~2.2T tokens, adopted as IBM's Granite 4 flagship, and led the post-training pipeline for a 70B+ reasoning model, covering multi-round iterative SFT and GRPO-based RL across increasing context phases.
Reachable via LinkedIn or email. Open to conversations about LLM training infrastructure, agentic systems, and research roles.