About the job
Quizlet, Inc. supports millions of learners each month by combining cognitive science with advanced machine learning. The platform serves two-thirds of U. S. high school students and half of college students, powering over 2 billion learning interactions monthly. Quizlet’s mission centers on making education more personal and effective for students, professionals, and lifelong learners.
The AI & Data Platform team underpins Quizlet’s applied AI initiatives. This group develops and maintains the systems behind personalization, recommendations, the AI Coach, content generation, and emerging agentic experiences. The team oversees the full machine learning model lifecycle: data and feature engineering, training, evaluation, deployment, and inference. Reliability, speed, security, and observability guide their work. Their approach blends managed Google Cloud services, top vendor tools, open-source solutions, and custom internal abstractions to achieve efficient, reliable outcomes.
Role overview
The Senior Staff Engineer, AI Platform, is a senior individual contributor who defines the technical direction for Quizlet’s next generation of machine learning and large language model infrastructure. This hands-on role involves architecting core platform systems, steering build-versus-buy decisions, and collaborating with teams across Applied AI, Data Science, Product Engineering, and Infrastructure. The position sets standards for how models and LLM-driven systems are trained, evaluated, deployed, and governed at scale.
This role is well suited to an engineer who excels at the senior-staff level in large organizations but values the autonomy and impact of a smaller, cloud-native setting. The technology stack includes Google Cloud, Kubernetes and GKE, distributed training, MLflow workflows, data and feature platforms, online and asynchronous inference, and the evaluation and observability tools needed to operate predictive ML and LLM systems at scale.
Work location and schedule
This is an onsite position based in San Francisco, CA. Team members are expected in the office at least three days a week: Monday, Wednesday, and Thursday, to foster collaboration.

