Samin Arnob is a PhD computer science researcher and practitioner based in Montreal with eight years of experience bridging reinforcement learning and large language model reasoning. Currently a Member of Technical Staff at Cohere and a doctoral student at Mila/McGill, he has driven research internships and applied projects at Microsoft, Ubisoft Montréal, and Skyfall AI, shaping RL for autonomy and modular, parameter-efficient LLM architectures. His work spans high-impact applied RL (reward-free hierarchical model-based exploration, offline/sequential RL for game agents) and practical LLM improvements like sparse adapters and reasoning pipelines. Comfortable moving ideas from research roadmaps to prototyped systems, he brings both academic rigor and startup-focused execution to agentic and enterprise AI challenges. An understated strength is his ability to combine world-modeling in RL with LLM decision-making to tackle autonomy in real-world settings.
8 years of coding experience
5 years of employment as a software developer
Doctor of Philosophy - PhD Computer Science, Doctor of Philosophy - PhD Computer Science at McGill University
Contributions:2 PRs, 27 pushes, 1 branch in 4 years 2 months
pythondeep-learningproblemsmachine-learningsolved
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