Machine Learning Intern 2027 (Toronto)
About this role
Pinterest needs skilled technical talent to bridge the gap between complex algorithmic research and user-facing features on its visual discovery platform. The incoming Machine Learning Intern will address engineering and product challenges by building out ML-powered recommendation and search systems that help users find creative inspiration.
Working alongside product, engineering, and data teams, the intern will take ownership of a scoped technical project from initial problem framing through experimentation and implementation. Daily responsibilities involve gathering and analyzing data to train models, writing clean code, and applying techniques in natural language processing or graph-based modeling. Mentorship from experienced engineers provides guidance throughout the term.
Ideal candidates are graduate students currently pursuing a Master's or PhD in a quantitative discipline such as Computer Science, Statistics, or Machine Learning. Successful applicants bring foundational academic or project experience in applied AI, along with strong communication skills and the ability to navigate open-ended technical challenges.
What you will do
- Own a scoped machine learning project from problem definition through experimentation, implementation, and communication of results with team guidance.
- Contribute to applied machine learning and artificial intelligence research that informs Pinterest product experiences.
- Collect, analyze, and synthesize data to develop data-driven machine learning models.
- Write clean, efficient, and maintainable code supported by appropriate documentation and testing.
- Apply relevant machine learning techniques, including natural language processing or graph-based approaches, to modeling and ranking problems across discovery, ads, and search.
- Break down scoped technical problems, propose approaches, and implement solutions while collaborating closely with teammates.
What you need
- Currently working towards a Master's or PhD degree in Computer Science, Machine Learning, Natural Language Processing, Statistics, Information Sciences, or a related field.
- Demonstrated experience applying machine learning or artificial intelligence concepts through research, coursework, projects, or internships.
- Familiarity with machine learning domains such as ranking, computer vision, natural language processing, content recommendations, embeddings, or information retrieval.
- Experience with big data technologies and scalable real-time systems that process stream data.
- Proficiency in at least one systems language or machine learning framework.
- Strong communication skills and the ability to find solutions for open-ended problems as part of a team.
Benefits
- Relocation assistance
Skills and tech stack
Questions candidates ask
What is the work location and remote policy for this internship?
This onsite internship will be based in the Toronto office and requires a few days in the office. The role needs to be in the office for in-person collaboration two to three weekdays per week and therefore requires candidates to be within a commutable distance of Toronto.
What is the compensation for this role?
The minimum and maximum base salary range for this position is CA$8,000 to CA$8,600 monthly. Final salary is based on a number of factors including location, travel, relevant prior experience, or particular skills and expertise.
What tools and technologies will I work with?
The team utilizes big data technologies and scalable real-time systems that process stream data, along with systems languages or machine learning frameworks like Hadoop, Spark, Java, C++, Python, Tensorflow, Pytorch, and MLFlow.
What is the interview process like regarding AI?
The company explores foundational skills and how candidates collaborate with AI. What matters most during the interview process is that applicants can always explain their approach, showing not just what they know, but how they think.
Who is eligible to apply for this position?
This posting is open to Canada-based applicants only who are working towards a Master's or PhD degree in Computer Science, ML, NLP, Statistics, Information Sciences, or a related field.