We are seeking a highly skilled Senior Machine Learning Engineer to lead the design, development, and implementation of advanced machine learning systems. In this role, you will be instrumental in analyzing complex datasets and building deep learning models, with a specialized focus on Natural Language Processing (NLP). You will leverage state-of-the-art transformer models to solve business challenges, optimize model performance, and track impact through robust metrics. The ideal candidate is a technical expert capable of translating business objectives into scalable ML solutions while mentoring teams and managing the end-to-end model lifecycle.
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Location: Toronto, ON ( 5 days onsite)
Contract Duration: 11-month contract
Rate: $414-$451.98/diem
Advantages
Advanced Tech Stack: Opportunity to work with cutting-edge NLP and Deep Learning architectures.
High-Impact Projects: Lead the development of models that directly influence business objectives and outcomes.
Collaborative Environment: Work within a cross-functional team focused on innovation and technical excellence.
Professional Stability: Long-term 11-month contract to drive significant ML initiatives from start to finish.
Responsibilities
Model Development: Design, develop, and implement advanced machine learning and deep learning systems.
NLP Specialization: Utilize NLP techniques—specifically BERT and transformer-based models—for text classification, sentiment analysis, and language understanding.
Data Strategy: Analyze data to identify relations between inputs and outputs; supervise data acquisition, cleaning, and preprocessing to ensure high-quality training sets.
Experimentation & Testing: Run machine learning tests and experiments, ranking algorithms by success probability to solve specific business problems.
Optimization: Fine-tune models and perform hyperparameter optimization, carefully balancing model complexity with performance trade-offs.
Lifecycle Management: Manage the full ML lifecycle, including feature engineering, data distribution analysis, and deployment strategies.
Cross-Functional Collaboration: Partner with stakeholders to define business objectives, ensure alignment with strategic goals, and provide reporting on model performance metrics.
Resource Management: Supervise project resources (hardware, data, personnel) to ensure deadlines are met in a fast-paced environment.
Qualifications
ML Proficiency: Deep understanding of fundamental machine learning concepts, algorithms, and techniques.
NLP Expertise: Significant knowledge of NLP models, including BERT and other transformers, for complex language tasks.
Framework Proficiency: Expert-level skill in deep learning libraries, specifically TensorFlow or PyTorch.
Programming Skills: Strong Python programming capabilities, with hands-on experience using NumPy, Pandas, and Scikit-learn.
Data Skills: Proficient in text preprocessing, tokenization, word embeddings, and data visualization.
Optimization: Demonstrated success in model optimization, hyperparameter tuning, and adapting pre-trained models via transfer learning.
Analytical Capability: Proven experience identifying data quality issues, defining validation strategies, and solving complex problems with ranked algorithmic solutions.
Soft Skills: Exceptional client relationship management, ability to manage competing priorities, and a proven track record of meeting strict deadlines.
Summary
If you're interested in the Senior Machine Learning Engineer role based in Toronto, we encourage you to apply online at www.randstad.ca. Only qualified candidates will be contacted for the next steps. We look forward to hearing from you!
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.
This posting is for existing and upcoming vacancies.
show more
We are seeking a highly skilled Senior Machine Learning Engineer to lead the design, development, and implementation of advanced machine learning systems. In this role, you will be instrumental in analyzing complex datasets and building deep learning models, with a specialized focus on Natural Language Processing (NLP). You will leverage state-of-the-art transformer models to solve business challenges, optimize model performance, and track impact through robust metrics. The ideal candidate is a technical expert capable of translating business objectives into scalable ML solutions while mentoring teams and managing the end-to-end model lifecycle.
Location: Toronto, ON ( 5 days onsite)
Contract Duration: 11-month contract
Rate: $414-$451.98/diem
Advantages
Advanced Tech Stack: Opportunity to work with cutting-edge NLP and Deep Learning architectures.
High-Impact Projects: Lead the development of models that directly influence business objectives and outcomes.
Collaborative Environment: Work within a cross-functional team focused on innovation and technical excellence.
Professional Stability: Long-term 11-month contract to drive significant ML initiatives from start to finish.
...
Responsibilities
Model Development: Design, develop, and implement advanced machine learning and deep learning systems.
NLP Specialization: Utilize NLP techniques—specifically BERT and transformer-based models—for text classification, sentiment analysis, and language understanding.
Data Strategy: Analyze data to identify relations between inputs and outputs; supervise data acquisition, cleaning, and preprocessing to ensure high-quality training sets.
Experimentation & Testing: Run machine learning tests and experiments, ranking algorithms by success probability to solve specific business problems.
Optimization: Fine-tune models and perform hyperparameter optimization, carefully balancing model complexity with performance trade-offs.
Lifecycle Management: Manage the full ML lifecycle, including feature engineering, data distribution analysis, and deployment strategies.
Cross-Functional Collaboration: Partner with stakeholders to define business objectives, ensure alignment with strategic goals, and provide reporting on model performance metrics.
Resource Management: Supervise project resources (hardware, data, personnel) to ensure deadlines are met in a fast-paced environment.
Qualifications
ML Proficiency: Deep understanding of fundamental machine learning concepts, algorithms, and techniques.
NLP Expertise: Significant knowledge of NLP models, including BERT and other transformers, for complex language tasks.
Framework Proficiency: Expert-level skill in deep learning libraries, specifically TensorFlow or PyTorch.
Programming Skills: Strong Python programming capabilities, with hands-on experience using NumPy, Pandas, and Scikit-learn.
Data Skills: Proficient in text preprocessing, tokenization, word embeddings, and data visualization.
Optimization: Demonstrated success in model optimization, hyperparameter tuning, and adapting pre-trained models via transfer learning.
Analytical Capability: Proven experience identifying data quality issues, defining validation strategies, and solving complex problems with ranked algorithmic solutions.
Soft Skills: Exceptional client relationship management, ability to manage competing priorities, and a proven track record of meeting strict deadlines.
Summary
If you're interested in the Senior Machine Learning Engineer role based in Toronto, we encourage you to apply online at www.randstad.ca. Only qualified candidates will be contacted for the next steps. We look forward to hearing from you!
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.
This posting is for existing and upcoming vacancies.
show more
