Senior Research Scientist LLM Agent Safety, Red-Teaming, Evaluation & Post-Training
Montreal, Quebec, Canada
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Summary
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Rockstar
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Top School
Gabriel Huang is a senior research scientist specializing in LLM agent safety, red-teaming, evaluation, and post-training workflows, with 11 years of applied ML experience and a PhD from Mila. At ServiceNow Research he builds end-to-end systems—DoomArena and TapeAgents—for stress-testing agentic systems against prompt-injection, adversarial tool interactions, and realistic enterprise constraints. He bridges research and engineering by designing attack/evaluation harnesses, calibrating LLM-as-a-judge pipelines, and operationalizing distillation and RLHF-style loops into reusable tooling. His background spans multimodal pretraining, self-supervised learning, and startup productization, giving him a rare blend of theoretical depth and production focus. Based in Montréal as a Canadian permanent resident, he is trilingual (native French, bilingual English, fluent Mandarin) and mentors graduate researchers while publishing reproducible benchmarks and frameworks.
11 years of coding experience
6 years of employment as a software developer
Master of Engineering (M.Eng.), Mathematics and Computer Science, Master of Engineering (M.Eng.), Mathematics and Computer Science at CentraleSupélec
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