Job description
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.
Job 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.
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