
Job description
Our team has an immediate 12-month co-op opening for an Engineer.
About the team:
Established in 2014, the Distributed Scheduling and Data Engine Lab is Huawei Cloud's technical innovation center in Canada. The lab focuses on researching and developing advanced cloud technologies, supporting the productization and iterative optimization of its technical achievements. Current research areas include cloud native databases, infrastructure resource scheduling and prediction, cloud-native middleware, media engines, and user experience studies. The lab fosters a robust technical environment, allowing collaboration with industry experts to create a highly competitive cloud platform.
About the role:
Support preparation and augmentation of datasets for training deep learning models, ensuring data quality and relevance.
Develop, test, and deploy AI modules and prototypes using Python.
Assist with research and experimentation on emerging AI techniques and technologies (e.g., LLMs, agentic AI, NLP).
Collaborate closely with team members to align on project goals, share insights, and contribute to an agile development process.
Job requirements
About the ideal candidate:
Currently enrolled in a university and participating in the school's co-op program (undergrad degree).
Strong foundation in algorithms, data structures, and object-oriented programming, with proficiency in Python (knowledge of R or Java is a plus).
Familiarity with ML and data analysis tools/libraries such as NumPy, Pandas, Matplotlib, and scikit-learn, along with basic understanding of statistics.
Exposure to deep learning concepts and frameworks, preferably PyTorch, and an interest in applying them to NLP or generative AI tasks.
Curiosity about NLP methods (NLU, NLG, transformers) and experience with libraries such as SpaCy or NLTK is a plus.
Interest in generative AI tools and techniques, including Large Language Models (LLMs), prompt engineering, and LLM-based AI agents.
Familiarity with (or willingness to learn about) cloud platforms and integration services such as Azure Logic Apps.
Passionate about learning and experimenting with new AI technologies, and able to work independently while contributing as a collaborative team member.
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