About Pinterest:

Millions of people across the world come to Pinterest to find new ideas every day. It’s where they get inspiration, dream about new possibilities and plan for what matters most. Our mission is to help those people find their inspiration and create a life they love. In your role, you’ll be challenged to take on work that upholds this mission and pushes Pinterest forward. You’ll grow as a person and leader in your field, all the while helping Pinners make their lives better in the positive corner of the internet.

Creating a life you love also means finding a career that celebrates the unique perspectives and experiences that you bring. As you read through the expectations of the position, consider how your skills and experiences may complement the responsibilities of the role. We encourage you to think through your relevant and transferable skills from prior experiences.

Our new progressive work model is called PinFlex, a term that’s uniquely Pinterest to describe our flexible approach to living and working. Visit our PinFlex landing page to learn more.

As a Machine Learning Intern within Pinterest, you’ll work on tackling new challenges in machine learning and artificial intelligence. Throughout your internship, you’ll join our engineering teams as we maneuver through exponential growth and massive scale while building awesome products and features, creating visually rich experiences, spearheading the discovery problem, and pinpointing tomorrow’s engineering challenges. Our fall internship will run between September 3 and December 6, 2024.

What you’ll do:

Contribute in cutting-edge research in machine learning and artificial intelligence that can be applied to Pinterest problems
Collect, analyze, and synthesize findings from data and build intelligent data-driven model
Write clean, efficient, and sustainable code
Use machine learning, natural language processing, and graph analysis to solve modeling and ranking problems across discovery, ads and search
Scope and independently solve moderately complex problems
Take proactive ownership over the completion and quality of your tasks and project with minimal guidance from your mentor, manager, and peers

What we are looking for:

Working towards a Master's or PhD in Computer Science, ML, NLP, Statistics, Information Sciences or related field
Machine Learning (ranking, computer vision, NLP, content recommendations, embedding, information retrieval etc all ok)
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)
Strong communicator and team player. Being able to find solutions for open-ended problems

Relocation Statement:

This position is not eligible for relocation assistance and requires periodical attendance at our Toronto office. Visit our PinFlex page to learn more about our working model.

#LI-REMOTE

#LI-FILS

Information regarding the culture at Pinterest and benefits available for this position can be found here.

Our Commitment to Diversity:

Pinterest is an equal opportunity employer and makes employment decisions on the basis of merit. We want to have the best qualified people in every job. All qualified applicants will receive consideration for employment without regard to race, color, ancestry, national origin, religion or religious creed, sex (including pregnancy, childbirth, or related medical conditions), sexual orientation, gender, gender identity, gender expression, age, marital status, status as a protected veteran, physical or mental disability, medical condition, genetic information or characteristics (or those of a family member) or any other consideration made unlawful by applicable federal, state or local laws. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. If you require an accommodation during the job application process, please notify accessibility@pinterest.com for support.

Machine Learning Intern 2024 (Toronto)

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