Machine Learning Intern Fall 2026 (Toronto)
PinterestToronto, ON, CAPosted 4 March 2026
Tech Stack
Job Description
<div class="content-intro"><p><strong>About Pinterest:</strong></p>
<p>Millions of people around the world come to our platform to find creative ideas, dream about new possibilities and plan for memories that will last a lifetime. At Pinterest, we’re on a mission to bring everyone the inspiration to create a life they love, and that starts with the people behind the product.</p>
<p>Discover a career where you ignite innovation for millions, transform passion into growth opportunities, celebrate each other’s unique experiences and embrace the <a href="https://www.pinterestcareers.com/our-life/pinflex/">flexibility</a> to do your best work. Creating a career you love? It’s Possible.</p></div><p>With more than 550 million users around the world and 300 billion ideas saved, Pinterest Machine Learning interns help build personalized experiences to help Pinners create a life they love. With just over 3,000 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.</p>
<p><strong><br>Note to applicants:</strong></p>
<p><strong>By applying to this role, you will be considered for multiple intern roles open across our various ML teams. Please only apply once as multiple applications may delay our recruitment process.</strong></p>
<p>As a Machine Learning Intern at 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. </p>
<p><strong><br>What you’ll do:</strong></p>
<ul>
<li>Lead your own project start to finish to contribute in cutting-edge research in machine learning and artificial intelligence that can be applied to Pinterest problems</li>
<li>Collect, analyze, and synthesize findings from data and build intelligent data-driven models</li>
<li>Write clean, efficient, and sustainable code</li>
<li>Use machine learning, natural language processing, and graph analysis to solve modeling and ranking problems across discovery, ads and search</li>
<li>Scope and independently solve moderately complex problems</li>
<li>Demonstrate accountability for the quality and completion of your tasks and projects, collaborating with your team and seeking guidance as needed</li>
</ul>
<p><strong><br>What we are looking for:</strong></p>
<ul>
<li>Working towards a <strong>Master's or PhD degree</strong> in Computer Science, ML, NLP, Statistics, Information Sciences or related field</li>
<li>Machine Learning (ranking, computer vision, NLP, content recommendations, embedding, information retrieval etc)</li>
<li>Experience with big data technologies (e.g., Hadoop/Spark) and scalable realtime systems that process stream data</li>
<li>Proficiency in at least one systems language (Java, C++, Python) or one ML framework (Tensorflow, Pytorch, MLFlow)</li>
<li>Experience in research and in solving analytical problems</li>
<li>Strong communicator and team player with the ability to find solutions for open-ended problems</li>
</ul>
<p><strong>Why Intern at Pinterest?</strong></p>
<ul>
<li>Meaningful Work: Contribute to projects that impact millions of users worldwide.</li>
<li>Mentorship: Learn from and be guided by experienced engineers and researchers in the field.</li>
<li>Growth and Development: Participate in professional development workshops and networking events to build your skills and connections.</li>
</ul>
<p>This job posting is for an open vacancy. Please note that the company utilizes artificial intelligence to screen applicants for the positions.</p>
<p>This onsite internship will be based in our Toronto office requiring a few days in office. Our pro ... (truncated, view full listing at source)
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