The Machine Learning Engineer role focuses on building and optimizing advanced machine learning models with an emphasis on natural language processing (NLP). The engineer will apply transformer-based models like BERT to tasks such as sentiment analysis and text classification. Responsibilities include data preprocessing, model development, hyper
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parameter tuning, and leveraging transfer learning techniques. This position also involves experimenting with deep learning frameworks like TensorFlow and PyTorch and using Python libraries such as NumPy, Pandas, and Scikit-learn. The role contributes to data-driven decision-making by designing systems that align with business objectives and measurable outcomes.
Advantages
•Hands-on experience with cutting-edge technologies like BERT and transformer models
•Opportunity to lead deep learning and NLP model development
•Involvement in real-world model deployment and optimization
•Use of popular tools like TensorFlow, PyTorch, Python, and Scikit-learn
•Chance to work with diverse datasets and explore transfer learning applications
Responsibilities
•Design, develop, and test machine learning and deep learning systems
•Implement and fine-tune BERT and transformer models for NLP tasks
•Conduct data preprocessing, including tokenization and word embeddings
•Analyze and visualize data to understand distribution and quality
•Optimize models through hyperparameter tuning and validation strategies
•Define preprocessing and feature engineering pipelines
•Ensure model performance in real-world deployment scenarios
•Support data acquisition and identify suitable online datasets
Qualifications
•Proficiency in machine learning fundamentals, algorithms, and concepts
•Expertise in NLP, including BERT and other transformer-based models
•Hands-on experience with TensorFlow or PyTorch
•Strong Python programming with NumPy, Pandas, and Scikit-learn
•Knowledge of model tuning, transfer learning, and performance trade-offs
•Background in statistics and computer programming
Summary
This role offers a chance to shape advanced AI-driven solutions with a strong focus on NLP and deep learning. Ideal for professionals with expertise in BERT, Python, and cloud-based ML tools, it provides the opportunity to work on impactful machine learning initiatives from design to deployment.
Randstad Canada is committed to fostering a workforce reflective of all peoples of Canada. As a result, we are committed to developing and implementing strategies to increase the equity, diversity and inclusion within the workplace by examining our internal policies, practices, and systems throughout the entire lifecycle of our workforce, including its recruitment, retention and advancement for all employees. In addition to our deep commitment to respecting human rights, we are dedicated to positive actions to affect change to ensure everyone has full participation in the workforce free from any barriers, systemic or otherwise, especially equity-seeking groups who are usually underrepresented in Canada's workforce, including those who identify as women or non-binary/gender non-conforming; Indigenous or Aboriginal Peoples; persons with disabilities (visible or invisible) and; members of visible minorities, racialized groups and the LGBTQ2+ community.
Randstad Canada is committed to creating and maintaining an inclusive and accessible workplace for all its candidates and employees by supporting their accessibility and accommodation needs throughout the employment lifecycle. We ask that all job applications please identify any accommodation requirements by sending an email to accessibility@randstad.ca to ensure their ability to fully participate in the interview process.
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The Machine Learning Engineer role focuses on building and optimizing advanced machine learning models with an emphasis on natural language processing (NLP). The engineer will apply transformer-based models like BERT to tasks such as sentiment analysis and text classification. Responsibilities include data preprocessing, model development, hyperparameter tuning, and leveraging transfer learning techniques. This position also involves experimenting with deep learning frameworks like TensorFlow and PyTorch and using Python libraries such as NumPy, Pandas, and Scikit-learn. The role contributes to data-driven decision-making by designing systems that align with business objectives and measurable outcomes.
Advantages
•Hands-on experience with cutting-edge technologies like BERT and transformer models
•Opportunity to lead deep learning and NLP model development
•Involvement in real-world model deployment and optimization
•Use of popular tools like TensorFlow, PyTorch, Python, and Scikit-learn
•Chance to work with diverse datasets and explore transfer learning applications
Responsibilities
•Design, develop, and test machine learning and deep learning systems
...
•Implement and fine-tune BERT and transformer models for NLP tasks
•Conduct data preprocessing, including tokenization and word embeddings
•Analyze and visualize data to understand distribution and quality
•Optimize models through hyperparameter tuning and validation strategies
•Define preprocessing and feature engineering pipelines
•Ensure model performance in real-world deployment scenarios
•Support data acquisition and identify suitable online datasets
Qualifications
•Proficiency in machine learning fundamentals, algorithms, and concepts
•Expertise in NLP, including BERT and other transformer-based models
•Hands-on experience with TensorFlow or PyTorch
•Strong Python programming with NumPy, Pandas, and Scikit-learn
•Knowledge of model tuning, transfer learning, and performance trade-offs
•Background in statistics and computer programming
Summary
This role offers a chance to shape advanced AI-driven solutions with a strong focus on NLP and deep learning. Ideal for professionals with expertise in BERT, Python, and cloud-based ML tools, it provides the opportunity to work on impactful machine learning initiatives from design to deployment.
Randstad Canada is committed to fostering a workforce reflective of all peoples of Canada. As a result, we are committed to developing and implementing strategies to increase the equity, diversity and inclusion within the workplace by examining our internal policies, practices, and systems throughout the entire lifecycle of our workforce, including its recruitment, retention and advancement for all employees. In addition to our deep commitment to respecting human rights, we are dedicated to positive actions to affect change to ensure everyone has full participation in the workforce free from any barriers, systemic or otherwise, especially equity-seeking groups who are usually underrepresented in Canada's workforce, including those who identify as women or non-binary/gender non-conforming; Indigenous or Aboriginal Peoples; persons with disabilities (visible or invisible) and; members of visible minorities, racialized groups and the LGBTQ2+ community.
Randstad Canada is committed to creating and maintaining an inclusive and accessible workplace for all its candidates and employees by supporting their accessibility and accommodation needs throughout the employment lifecycle. We ask that all job applications please identify any accommodation requirements by sending an email to accessibility@randstad.ca to ensure their ability to fully participate in the interview process.
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