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Graph Machine Learning Jobs in Toronto, ON (NOW HIRING)

Tiger Analytics Inc.

Knowledge Graph SME

Toronto, ON · On-site

Our consultants bring deep expertise in Data Science, Machine Learning, and AI. Our business value ... We are seeking a Senior Knowledge Graph SME to lead the architecture, design, and implementation of ...

Tiger Analytics Inc.

Knowledge Graph SME

Toronto, ON · On-site

Our consultants bring deep expertise in Data Science, Machine Learning, and AI. Our business value ... We are seeking a Senior Knowledge Graph SME to lead the architecture, design, and implementation of ...

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All JobsGraph Machine Learning JobsGraph Machine Learning Jobs in Toronto, ON

Graph Machine Learning information

What is the difference between Graph Machine Learning vs Data Scientist?

AspectGraph Machine LearningData Scientist
Required CredentialsDegree in Computer Science, Data Science, or related fields; knowledge of graph theory and machine learningDegree in Statistics, Computer Science, or related fields; proficiency in data analysis and programming
Work EnvironmentResearch labs, tech companies, AI startups focusing on graph dataBusiness, finance, healthcare, and tech industries analyzing diverse data sets
Industry UsageSpecialized in graph data analysis and machine learning models on graph structuresBroad data analysis, modeling, and insights across various sectors

Graph Machine Learning focuses on developing algorithms for graph-structured data, while Data Scientists analyze and interpret diverse data sets across industries. Both roles require strong analytical skills, but their focus areas and tools differ significantly.

Infographic showing various Graph Machine Learning job openings in Toronto, ON as of September 2026, with employment types broken down into 25% Internship, and 75% Full Time. Highlights an 50% In-person, 25% Hybrid, and 25% Remote job distribution.

Machine Learning Engineer II, Core Engineering

Toronto, ON • Remote

Pinterest
Internet and IT • 1 - 5K employees
Learn more about Pinterestexternal

Full-time

Re-posted 19 days ago

Job description

With more than 500 million users around the world and 300 billion ideas saved, Pinterest Machine Learning engineers build personalized experiences to help Pinners create a life they love. With just over 4,000 global employees, our teams are small, mighty, and still growing. At Pinterest, you'll experience hands-on access to an incredible vault of data and contribute large-scale recommendation systems in ways you won't find anywhere else.

What you'll do:

  • Build cutting edge technology using the latest advances in deep learning and machine learning to personalize Pinterest
  • Partner closely with teams across Pinterest to experiment and improve ML models for various product surfaces (Homefeed, Ads, Growth, Shopping, and Search), while gaining knowledge of how ML works in different areas
  • Use data driven methods and leverage the unique properties of our data to improve candidates retrieval
  • Work in a high-impact environment with quick experimentation and product launches
  • Keeping up with industry trends in recommendation systems 

What we're looking for:

  • 2+ years of industry experience applying machine learning methods (e.g., user modeling, personalization, recommender systems, search, ranking, natural language processing, reinforcement learning, and graph representation learning)
  • End-to-end hands-on experience with building data processing pipelines, large scale machine learning systems, and big data technologies (e.g., Hadoop/Spark)
  • M.S. or PhD in Machine Learning or related areas
  • Expertise in scalable realtime systems that process stream data
  • Passion for applied ML and the Pinterest product

Nice To Have:

  • Experience using Cursor, Copilot, Codex, or similar AI coding assistants for development, debugging, testing, and refactoring.
  • Familiarity with LLM-powered productivity tools for documentation search, experiment analysis, SQL/data exploration, and engineering workflow acceleration.

This job posting is for an open vacancy. Please note that the company utilizes artificial intelligence to screen applicants for the positions.

Relocation Statement: 

  •  This position is not eligible for relocation assistance. Visit our PinFlex page to learn more about our working model.

In-Office Requirement Statement:

  • We let the type of work you do guide the collaboration style. That means we're not always working in an office, but we continue to gather for key moments of collaboration and connection.

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