Senior/Staff AI & Data Platform Engineer, Quizlet

• This role requires strong technical depth, strategic thinking, and the ability to deliver systems that accelerate ML and Data innovation
• 5-8+ years of experience building and maintaining large-scale data or ML platforms in production environments
• Experience contributing to team-wide best practices and advocating for reliability and efficiency in data workflows
• Deep experience with distributed systems, data pipelines, and ML infrastructure (e.g., Airflow, dbt, GCP, Kubernetes, feature stores)
• Excellent communication skills with the ability to influence and align diverse stakeholders

Desirable

• The AI & Data Platform team's mission is to build and maintain a rock-solid, scalable, and efficient foundation for all data and machine learning operations at Quizlet
• This team is the bedrock upon which our AI ambitions are built
• As we consolidate our AI efforts to create a unified and powerful product portfolio, the platform team's primary focus is on achieving operational excellence
• We aggressively buy and leverage best-in-class MLOps and DataOps technologies to accelerate the pace of innovation across Quizlet
• As an AI & Data Platform Engineer, you will help lead the design and development of Quizlet’s analytical data and machine learning infrastructure, ensuring our platforms are scalable, reliable, and designed for long-term success
• You’ll partner closely with cross-functional teams to define technical direction, guide architectural decisions, and mentor engineers across Data Science, ML Engineering, and Product
• You will measure success through platform adoption, reliability improvements, and developer productivity outcomes
• Accelerate and amplify the work of our Machine Learning Engineers by building ML infrastructure that streamlines the development, testing, and deployment of machine learning models to production
• Collaborate with cross-functional teams, including Product Management, Data Analytics, and Product Engineering, to build systems that support a diverse range of data needs
• Build tools and services that improve developer efficiency and platform usability
• Enable the ingestion and processing of large-scale data, from real-time streaming to batch processing, by developing and implementing scalable and resilient services, platform, and infrastructure
• Own projects end-to-end, from conceptualization to launch and deployment
• Partner with Product Engineers and Data Scientists to ensure that critical data is delivered to its destination with maximum availability, recoverability, and operational efficiency
• Design and deliver reliable data and ML infrastructure, contributing to the team’s roadmap and collaborating across functions to enable data-driven features and insights