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Intern Researcher - Reinforcement Learning and LLM

    • Vancouver, British Columbia
  • ackvs

Job description

Huawei Canada has an immediate 12-month internship opening for an Intern Researcher.

About the team:

The Big Data and Intelligence Platform lab is focused on advancing core AI technologies for the Cloud, utilizing large language models (LLMs) to tackle complex real-world challenges across various sectors. Composed of researchers with advanced degrees from top Canadian universities, this lab specializes in integrating LLMs for operations research, analytical databases, and data systems, optimizing efficiency within LLM architectures. This lab prioritizes responsible AI practices, including data watermarking and federated learning. Committed to academic excellence, findings are published in leading conferences, shaping the future of AI technology and contributing to the scientific community.

About the job:

  • Conduct cutting-edge research in large language models (LLMs), focusing on agent-building technologies.

  •  Leverage reinforcement learning techniques to enhance agent performance in specialized business applications.

  •  Design, develop and maintain research prototypes, ensuring comprehensive documentation and adherence to software development best practices.

  •  Contribute to publishing full research papers in top-tier conferences and journals.

The target annual compensation (based on 2080 hours per year) ranges from $93,000 to $104,000 depending on education, experience and demonstrated expertise.

Job requirements

About the ideal candidate:

  • PhD in Computer Science, Artificial Intelligence, Machine Learning, Mathematics, or a closely related technical field.

  • Proficient in Python programming with significant experience in model development and optimization.

  • Excellent analytical, problem-solving, and troubleshooting abilities with a focus on delivering innovative research solutions.

  •  Strong written and verbal communication skills, with the ability to collaborate effectively within a team.

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