University Grad Machine Learning Engineer 2027 (Toronto)

As a Machine Learning Engineer at Pinterest, you’ll develop and improve machine learning systems that power product experiences and discovery. You’ll partner with engineering, product and design teams to build, evaluate and iterate on scalable solutions that help Pinners find relevant, inspiring content. In this role, you’ll grow your technical expertise while contributing to reliable, high-impact systems.

What you’ll do:

• Conduct applied machine learning research to address product and platform challenges at Pinterest.
• Collect, analyze and synthesize data to develop data-driven machine learning models.
• Write maintainable, efficient code and contribute to testing and code-review practices.
• Apply machine learning techniques, including natural language processing and graph-based approaches, to modeling and ranking challenges across discovery, ads and search.
• Design, build and test recommendation and engagement-prediction models that improve push, email and in-app notification experiences.
• Develop and iterate on large-scale applied machine learning systems, using evaluation results to improve model performance and reliability.
• Scope, implement and deliver solutions for moderately complex ML problems, escalating risks and tradeoffs as needed.
• Experience applying machine learning or AI concepts through research, coursework, projects or internships.
• Use AI to accelerate analysis and iteration while applying judgment and verification to ensure correctness and quality.

What we’re looking for:

• Master's in Computer Science, ML, NLP, Statistics, Information Sciences or related field required
• Machine Learning experience (ranking, computer vision, NLP, content recommendations, embedding, information retrieval etc)
• Experience with big data technologies (e.g., Hadoop/Spark) and scalable realtime systems that process stream data
• Mastery of at least one systems languages (Java, C++, Python) or one ML framework (Tensorflow, Pytorch, MLFlow)
• Cross-functional collaborator and strong communicator
• Comfortable solving ambiguous problems and adapting to a dynamic environment
• Experience in research and in solving analytical problems

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

In-Office Requirement:

• This onsite internship will be based in our Toronto office requiring a few days in office. Our program will run in a full-time capacity during typical business hours between Monday-Friday.
• This role will need to be in the office for in-person collaboration 2-3 weekdays per week and therefore needs to be within a commutable distance of Toronto.

Relocation Statement:

• This position may be eligible for relocation assistance. Visit our PinFlex page to learn more about our working model.
• Information regarding the culture at Pinterest and benefits available for this position can be found here.

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