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 workplace feedback
Study RLHF, GRPO, and reward-free post-training methods
Develop reinforcement learning for tool-using and browsing agents
Design multi-turn, verifiable reasoning evaluation tasks
Scale experiments across large GPU clusters and publish insights
Requirements: PhD in Computer Science or related field, or comparable master’s experience
Strong deep learning foundation, including Transformers and optimization
Research experience in reinforcement learning or language model fine-tuning
First-author paper at a listed top-tier AI venue
Python, PyTorch, DeepSpeed, and distributed training proficiency
Apply reinforcement learning, distributed training, and evaluation expertise to advancing reasoning-enhanced LLM research at Huawei Canada.