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 environment 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

Solid 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.

📌 Reinforcement Learning Researcher LLMs (Winnipeg)
🏢 Huawei Technologies
📍 Winnipeg