About the job
About Quizlet:
At Quizlet, we are dedicated to empowering every learner to achieve their educational goals in the most effective and enjoyable manner. Our $1B+ learning platform supports millions of students monthly, including two-thirds of U.S. high schoolers and half of U.S. college students, facilitating over 2 billion learning interactions each month.
By merging cognitive science with advanced machine learning techniques, we enhance and personalize the learning journey for students, professionals, and lifelong learners. We are inspired by the opportunity to support an ever-growing number of learners with diverse approaches and tools.
Let’s Shape the Future of Learning Together
Join us in crafting and delivering AI-driven learning tools that scale globally and unlock human potential.
About the Team:
The Personalization & Recommendations ML Engineering team creates the foundational intelligence that enables Quizlet to connect learners with the content, activities, and experiences that best align with their goals. We drive recommendation and search systems across various platforms, from home feeds and search results to adaptive study modes.
Our aim is to ensure Quizlet feels uniquely customized for each learner by integrating cutting-edge machine learning, scalable infrastructure, and insights from learning science.
You will collaborate closely with product managers, data scientists, platform engineers, and fellow ML engineers to develop personalized learning pathways that enhance engagement, satisfaction, and tangible learning outcomes.
About the Role:
As a Senior Machine Learning Engineer on the Personalization & Recommendations team, you will be responsible for designing, building, and optimizing large-scale retrieval, ranking, and recommendation systems that directly influence how learners discover and interact with Quizlet.
Your strong expertise in modern recommender systems—including deep learning-based retrieval, embeddings, multi-task ranking, and evaluation—will be pivotal in advancing Quizlet’s personalization capabilities.
Moreover, you will operate at the intersection of machine learning, product development, and scalable systems, ensuring our recommendations are efficient, responsible, and aligned with learner outcomes, privacy, and fairness.
We are excited to announce that this is an onsite position at our San Francisco office. To promote collaboration, we require employees to be in the office a minimum of three days a week: Monday, Wednesday, and Thursday, as well as additional days as needed by your manager or the company. We believe that this work environment fosters stronger team collaboration.