Huawei Technologies Canada Co., Ltd.
Co-op Researcher – LLM Post-Training & Agentic Coding
A co-op researcher at Huawei's Noah's Ark AI lab in Edmonton conducts cutting-edge research on LLM post-training, reinforcement learning, reasoning, and agentic coding — owning problems end-to-end from hypothesis to large-scale experiments, and building scalable GPU training, inference, and agent-evaluation infrastructure. Core stack: Python, PyTorch, and distributed LLM frameworks like vLLM, SGLa
- Compensation
- Not disclosed
- Location
- Edmonton, Canada
- Work setup
- Onsite
- Seniority
- Not specified
- Employment
- Internship
- Experience
- Not specified
- Category
- Ai engineering
- Posted
Skills
Must have
- Currently enrolled in a senior Bachelor's, Master's, or PhD program in Computer Science, Machine Learning, AI, or a related technical field, with strong fundamentals in machine learning and modern dee
- Strong understanding of large language models and modern post-training techniques (Transformer models, supervised fine-tuning, reinforcement learning, preference optimization, distillation, reasoning,
- Strong programming and software-engineering skills, particularly in Python and PyTorch, able to independently implement, debug, profile, and iterate on complex ML or agent systems
- Hands-on experience in one or more of: LLM post-training, coding or tool-using agents, reinforcement learning, large-scale model training/inference, distributed systems, or ML infrastructure
- Demonstrated ability to take an open-ended, ambiguous technical problem, design effective experiments or systems, and independently drive work toward measurable results
- Strong analytical and experimental judgment: designing controlled experiments, rigorous model evaluation, diagnosing unexpected behaviors, distinguishing genuine improvements from noise
- Self-motivated, intellectually curious, execution-oriented, with strong communication and collaboration skills in a rapid research iteration cycle
- Applicants must be enrolled in a co-op program and registered for an official co-op work term for the full duration of the employment period
Nice to have
- Strong assets: top-tier AI/ML publications or substantial research experience, impactful open-source or agent/LLM projects
- Hands-on experience with frameworks and systems such as vLLM, SGLang, FSDP, DeepSpeed, Hugging Face, Docker, Linux, Git, or multi-GPU compute environments
Full description
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.
Requirements
About the ideal candidate:
- Currently enrolled in a senior Bachelor’s, Master’s, or PhD program in Computer Science, Machine Learning, Artificial Intelligence, or a related technical field, with strong fundamentals in machine learning and modern deep learning.
- Strong understanding of large language models and modern post-training techniques, including Transformer-based models, supervised fine-tuning, reinforcement learning, preference optimization, distillation, reasoning, or synthetic-data-driven training.