Our team has an immediate 12-month co-op opening for an Engineer.

Responsibilities:

• Prepare and augment datasets for training deep learning models, ensuring data quality and relevance.
• Use Python to develop, test, and deploy AI modules and systems.

• Conduct research on rapidly evolving AI techniques and emerging technologies.
• Engage in close collaboration and interaction with members of the team to align on project goals and share insights throughout the development process.

Requirements

What you'll bring to the team:

• Currently enrolled in a university and participating in the school's co-op program (undergrad degree, a master degree is an asset).
• Strong foundation in algorithms, data structure, and object-oriented-programming along with proficiency in Python, R, and Java.
• Experience in using ML and exploratory data analysis (EDA) tools and libraries including Numpy, Pandas, Matplotlib, and scikit-learn, along with a good understanding of data statistics.
• In-depth knowledge of Artificial Neural Networks like CNN, RNN, LSTM, and GRU, along with expertise in DL frameworks such as PyTorch and TensorFlow.
• Solid understanding of various NLP tasks and concepts in both NLU (e.g, text/token classification) and NLG (e.g., text generation) domains as well as hands-on experience with NLP libraries like SpaCy, and NLTK.
• Theoretical knowledge of advanced NLP concepts including transformers, pre-training with self-supervised techniques, and transfer learning, along with experience in fine-tuning different types of Language Models (including encoder, decoder, and Seq2Seq) from Hugging Face.
• Knowledge of Generative AI tools and techniques including Large Language Models (LLMs), Prompt Engineering, Retrieval Augmented Generation (RAG), and LLM-based AI agents.
• Familiarity with cloud providers and cloud services, especially in the domain of Integration Platform as a Service (iPaaS), such as Azure Logic Apps Service.