AI Machine Learning Engineer for Advanced Data Solutions

1 day ago


Old Toronto, Canada Teranet Full time

Teranet, a leading provider of data-driven solutions, is seeking an experienced AI Machine Learning Engineer to join our dynamic team. This role plays a key part in designing, developing, and implementing cutting-edge machine learning models to drive business growth.

About Teranet

We are Canada's leader in delivering statutory registry services with expertise in land and commercial registries. Our company offers insightful property and data solutions, as well as practice management automation, to thousands of customers across various markets.

This role will be responsible for collaborating closely with stakeholders to understand business requirements and objectives of machine learning use cases. You will identify and acquire the best data sources available to meet use case objectives, explore data to build foundational data knowledge in subject domains, and develop tailored machine learning models.

Responsibilities
  • Design and develop cutting-edge machine learning models to address business needs
  • Collaborate with data scientists and engineers to implement models in the Big Data Platform using cloud technologies
  • Present technical analyses in a meaningful and intuitive manner to stakeholders
  • Document analysis processes, methods, and findings to meet quality standards and production requirements
  • Continuously monitor and fine-tune model performance by evaluating new or revised data sources, modeling techniques, and tools
What We Offer
  • $120,000 - $180,000 per year
  • A competitive pay structure
  • 100% Employer-Paid Health Benefit Plan
  • Retirement Savings Plans with Employer Matching Scheme
  • Ongoing Financial Wellness Seminars
  • Corporate Discounted Programs + Wellness Program
  • Employee Assistance Program (EAP) for our employees and their families
Requirements
  • 5+ years of experience in Python programming language with a strong emphasis on machine learning applications
  • Solid understanding of statistical concepts and their application in data science
  • Experience with data query languages such as SQL
  • Skills in data visualization tools, such as Tableau, for effective presentation of analytical findings
  • Strong knowledge of deep learning techniques and their practical applications

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