About the Team:

We are looking for Machine Learning Engineers ranging from the Senior to Staff levels (note: leveling decisions made through the interview process).

Our Machine Learning team builds the predictive and decisioning systems that power personalization, monetization, and learner engagement at Quizlet.
We focus on developing models and systems that drive real-time product decisions-balancing business outcomes with long-term learner success. This work is central to how we improve the learning experience for millions of users.
About the Role:

We're hiring Machine Learning Engineers across multiple levels, with leveling determined through the interview process.

In this role, you'll design, build, and deploy machine learning systems that power key product decisions-such as personalization, retention, monetization, and study guidance. You'll work across the full lifecycle, from modeling and experimentation to production integration and long-term system reliability.

Success is measured by your ability to deliver scalable ML systems that drive measurable product impact.

We're happy to share that this is an onsite position in either our Denver, San Francisco, Seattle, or NYC. To help foster team collaboration, we require that employees be in the office a minimum of three days per week: Monday, Wednesday, and Thursday and as needed by your manager or the company. We believe that this working environment facilitates increased work efficiency, team partnership, and supports growth as an employee and organization.

In this role, you will:

• Develop predictive and decisioning models (e.g., conversion, churn, LTV, personalization)
• Design and implement systems for real-time and batch inference
• Build end-to-end ML pipelines for training, evaluation, deployment, and monitoring
• Partner with Product, Engineering, and Data teams to define problems and deliver solutions
• Integrate ML systems into production environments with a focus on reliability and scalability
• Establish evaluation frameworks connecting offline metrics to online impact (A/B testing)
• Improve system performance across latency, throughput, and observability

What you bring to the table:

• Experience building and deploying ML systems in production
• Strong background in machine learning methods (e.g., predictive modeling, recommendation systems, or decisioning systems)
• Experience with data pipelines, model serving, and scalable systems
• Proficiency in Python and common ML frameworks
• Ability to operate across ambiguity and drive end-to-end solutions
• Strong collaboration and communication skills

Compensation, Benefits & Perks:

• Collaborate with your manager and team to create a healthy work-life balance
• 20 vacation days that we expect you to take!
• Competitive health, dental, and vision insurance (100% employee and 75% dependent PPO, Dental, VSP Choice)
• Employer-sponsored 401k plan with company match
• Access to LinkedIn Learning and other resources to support professional growth
• Paid Family Leave, FSA, HSA, Commuter benefits, and Wellness benefits
• 40 hours of annual paid time off to participate in volunteer programs of choice

#LI-onsite

We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.