Advance LLM learning through reinforcement learning research at Huawei Canada’s Noah’s Ark lab. This 12-month contract focuses on interactive environments.
The Reinforcement Learning Researcher will develop research for continual, agentic self-improvement beyond static fine-tuning. Work spans deep learning, Transformers, language model post-training, and interactive agents. You will implement and evaluate training and benchmarking pipelines for reasoning-enhanced LLMs and tool-using systems.
Key Responsibilities
Enable LLMs to learn from experience and setting feedbackStudy RLHF, GRPO, and reward-free post-training methodsDevelop reinforcement learning for tool-using and browsing agentsDesign multi-turn,
verifiable reasoning evaluation tasksScale experiments across large GPU clusters and publish insightsRequirements:
PhD in Computer Science or related field, or comparable master’s experienceStrong deep learning foundation, including Transformers and optimizationResearch experience in reinforcement learning or language model fine-tuningFirst-author paper at a listed top-tier AI venuePython, PyTorch, DeepSpeed, and distributed training proficiencyApply reinforcement learning, distributed training, and evaluation expertise to advancing reasoning-enhanced LLM research at Huawei Canada.