Co-op Researcher – LLM Post-Training & Agentic Coding

Huawei Canada has an immediate Co-op opening for a Researcher.

About the team:

Founded in 2012, the Noah’s Ark lab has evolved into a prominent research organization with notable achievements in academia and industry. The lab’s mission focuses on advancing artificial intelligence and related fields to benefit the company and society. Driven by impactful, long-term projects, the aim is to enhance state-of-the-art research while integrating innovations into the company's products and services, including Next Generation Foundation Model, Agentic Models, Physical AI and Reinforcement Learning.

About the job:

• Conduct cutting-edge research on LLM post-training, reinforcement learning, reasoning, agentic coding, and self-improving agents, with the opportunity to take technically challenging ideas from initial hypothesis to rigorous experimental validation.

• Develop new approaches for agent training, task and data synthesis, environment generation, scalable learning from interaction, and agent evaluation, with particular interest in terminal, repository-level, and software-engineering environments.

• Build and evaluate intelligent agents capable of reasoning, tool use, code generation and modification, and solving complex real-world tasks, while studying their capabilities, failure modes, and generalization behavior.

• Own research problems end-to-end, including literature review, problem formulation, experiment design, implementation, large-scale evaluation, analysis, and communicating high-quality research findings.

• Build reliable and scalable infrastructure for LLM training, inference, agent rollout, evaluation, and synthetic data generation, supporting rapid experimentation across large models and datasets.

• Improve the efficiency and reliability of GPU-based post-training and inference workflows, including distributed execution, resource utilization, debugging, automation, and day-to-day research compute operations.

• Work closely with researchers and engineering teams across Huawei to rapidly prototype new ideas, reproduce and extend state-of-the-art methods, and translate promising research advances into practical LLM systems and downstream projects.

• Contribute in a fast-moving, high-ownership research environment where a focused Co-op term can lead to meaningful research, engineering, open-source, or publication-quality contributions.