Senior Staff Machine Learning Engineer, Personalization & Recommendations

Senior Staff Machine Learning Engineer, Personalization & Recommendations

Location : San Francisco, CA. Employment type : Full‑time. Seniority level : Not applicable. Job function : Engineering and Information Technology. Industries : Software Development.

About Quizlet

At Quizlet, our mission is to help every learner achieve their outcomes in the most effective and delightful way. Our $1B+ learning platform serves tens of millions of students every month, including two-thirds of U.S. high schoolers and half of U.S. college students, powering over 2 billion learning interactions monthly.

About The Team

The Personalization & Recommendations ML Engineering team builds the core intelligence behind how Quizlet matches learners with content, activities, and experiences that best fit their goals. We power recommendation and search systems across multiple surfaces, from home feed and search results to adaptive study modes. Our team's objective is to make Quizlet feel uniquely tailored for every learner by combining cutting‑edge machine learning, scalable infrastructure, and insights from learning science.

About The Role

As a senior technical leader on the Personalization & Recommendations team, you’ll architect and implement large‑scale retrieval, ranking and recommendation systems that directly shape the learner experience. You’ll bring modern RecSys expertise and help evolve Quizlet’s personalization stack.

You’ll help define and deliver systems that learn from billions of interactions while respecting learner privacy, fairness and integrity.

This is an onsite position in our San Francisco office. Employees must be in the office a minimum of three days per week : Monday, Wednesday, and Thursday, as required by your manager or the company.

In This Role, You Will

• Work closely with senior leaders to define and drive the long‑term technical vision for personalization and recommendations across multiple Quizlet surfaces.
• Communicate complex modeling trade‑offs and recommendations to diverse audiences, influencing decisions through clear reasoning, data, and empathy.
• Architect and build large‑scale personalization models across candidate retrieval, ranking, and post‑ranking layers, leveraging user embeddings, contextual signals, and content features to power adaptive learning experiences.
• Develop scalable retrieval and serving systems using modern architectures such as Two‑Tower, deep ranking, and ANN‑based vector search for real‑time personalization at global scale.
• Lead model training, evaluation, and deployment pipelines for retrieval and ranking systems, ensuring training‑serving consistency, reliability, and robust monitoring.
• Partner closely with Product and Data Science to translate learning objectives into measurable modeling goals and experimentation frameworks.
• Advance evaluation methodologies by refining offline metrics and online A / B testing to rigorously measure learner impact and model performance.
• Collaborate with platform and infrastructure teams to optimize distributed training, inference latency, and cost‑efficient serving in production environments.
• Stay at the forefront of personalization and RecSys research, bringing relevant advances from top conferences into applied production systems.
• Mentor and coach engineers and applied scientists, fostering technical excellence, reproducibility, and responsible AI practices across the organization.
• Champion a culture of collaboration, inclusivity, and experimentation, helping elevate Quizlet’s AI craft and ensuring personalization systems serve learners equitably and effectively.

What You Bring To The Table

Bonus Points If You Have

Compensation, Benefits & Perks

Why Join Quizlet

We strive to make everyone feel comfortable and welcome. We work to create a holistic interview process, where both Quizlet and candidates have an opportunity to view what it would be like to work together, in exploring a mutually beneficial partnership. We provide a transparent setting that gives a comprehensive view of who we are.

In Closing

At Quizlet, we’re excited about passionate people joining our team—even if you don’t check every box on the requirements list. We value unique perspectives and believe everyone has something meaningful to contribute. Our culture is all about taking initiative, learning through challenges, and striving for high‑quality work while staying curious and open to new ideas. We believe in honest, respectful communication, thoughtful collaboration, and creating a supportive space where everyone can grow and succeed together. Quizlet’s success as an online learning community depends on a strong commitment to diversity, equity, and inclusion. As an equal opportunity employer, Quizlet welcomes applicants from all backgrounds. Women, people of color, members of the LGBTQ+ community, individuals with disabilities, and veterans are strongly encouraged to apply. Come join us!

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