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Machine Learning Specialist
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Machine Learning Specialist
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Data Ontologist
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Montréal, QC, Canada Intellibus Full timeAre you a Data Ontologist working at a Large Financial Institution and being told by your leadership that you are too hands-on or detail-oriented or think and work like a start-up? Imagine working at **Intellibus** to engineer platforms that impact billions of lives worldwide. With your passion and focus we will accomplish great things together! We look...
Machine Learning Engineer
3 months ago
Title: Machine Learning EnfgineerLocation: Montreal, QCDuration: 09 MonthsPay rate: $90/hr to $100/hr without any benefitsResponsibilities: The Machine Learning (ML) Expert will:• Understand the business needs and requirements and translate them into ML solutions.• Communicate technical concepts and results to non-technical stakeholders in a clear and concise manner.• Collaborate with internal clients to identify new opportunities for ML applications and models.• Ensure that ML Models are aligned with the bank’s overall strategy and goals. • Work with Application Development teams to deploy and support ML models in production environments. • Stay up to date with latest development in ML and AI and apply this knowledge to first improve the performances of applications (current & past), and second to the benefits of the team. Minimum Required Qualifications • Master’s degree in computer science, mathematics, statistics, or a related field. • Strong programming skills in languages such as Python, database manipulation (SQL), statistical modeling, and data analysis techniques. • Experience with machine learning frameworks such as Tensorflow, PyTorch, or scikit-learn. • Experience in developing and working on real-world machine learning projects. • Strong problem-solving and analytical skills. • Excellent communication (both French and English) and collaboration skills. • Very strong work ethic and ability to deal with confidential information. Nice-to-have Qualifications • Experience in deploying models to production. • Experience with CI/CD pipelines (GIT, Jenkins, …) and MLOps (MLFlow). • Experience with containerization techniques (Docker & Kubernetes). • Experience with mentoring junior team members.