Staff Machine Learning Engineer
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Job Location:
San Francisco, CA - USA
Monthly Salary:
$ 209920 - 285000
Posted on:
7 hours ago
Vacancies:
1 Vacancy
Job Summary
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.
We blend cognitive science with machine learning to personalize and enhance the learning experience for students professionals and lifelong learners alike. Were energized by the potential to power more learners through multiple approaches and various tools.
Lets Build the Future of Learning
Join us to design and deliver AI-powered learning tools that scale across the world and unlock human potential.
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 mission is to make Quizlet feel uniquely tailored for every learner by combining cutting-edge machine learning scalable infrastructure and insights from learning science.
Youll collaborate closely with product managers data scientists platform engineers and fellow ML engineers to deliver personalized learning pathways that drive engagement satisfaction and measurable learning outcomes.
About the Role:
As a Senior or Staff Machine Learning Engineer on the Personalization & Recommendations team youll design and build large-scale retrieval ranking and recommendation systems that directly shape how learners discover and engage with Quizlet.
Youll bring deep expertise in modern recommender systems from deep learningbased retrieval and embeddings to multi-task ranking and evaluation and help evolve Quizlets personalization stack to power adaptive effective learning experiences.
Youll work at the intersection of machine learning product design and scalable systems ensuring our recommendations are performant responsible and aligned with learner outcomes privacy and fairness.
Were happy to share that this is an onsite position in our San Francisco office. 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.
In this role you will:
- Design and implement personalization models across candidate retrieval ranking and post-ranking layers leveraging user embeddings contextual signals and content features
- Develop scalable retrieval and serving systems using architectures such as Two-Tower deep ranking and ANN-based vector search for real-time personalization across surfaces
- Build and maintain model training evaluation and deployment pipelines ensuring reliability trainingserving consistency and robust monitoring
- Partner closely with Product and Data Science to translate learner objectives (engagement retention mastery) into measurable modeling goals and experimentation plans
- Advance evaluation methodologies refining offline metrics (e.g. NDCG CTR calibration) and supporting rigorous A/B testing to measure learner and business impact
- Collaborate with platform and infrastructure teams to optimize distributed training inference latency and serving cost at scale
- Contribute to the long-term technical vision for personalization and recommendations aligning modeling strategy with Quizlets AI and product roadmaps
- Stay current with RecSys research and industry trends bringing relevant advances from top conferences (KDD WSDM SIGIR RecSys NeurIPS) into production
- Mentor other engineers and applied scientists fostering technical growth experimentation rigor and responsible ML practices
- Champion collaboration inclusion and curiosity helping build a team culture that values diverse perspectives and data-driven problem-solving
What you bring to the table:
- 10 years of experience in applied machine learning or ML-heavy software engineering with a strong focus on personalization ranking or recommendation systems
- Track record of measurable impact improving key online metrics such as CTR retention or engagement through recommender or search systems in production
- Strong hands-on skills in Python and PyTorch with expertise in data and feature engineering distributed training and inference on GPUs and familiarity with modern MLOps practices including model registries feature stores monitoring and drift detection
- Deep understanding of retrieval and ranking architectures including Two-Tower models deep cross networks Transformers or MMoE and how to apply them in production contexts
- Experience with large-scale embedding models and vector search (e.g. FAISS ScaNN) including training serving and optimization at scale
- Proficiency in experiment design and evaluation connecting offline metrics (AUC NDCG calibration) with online A/B test results to drive product decisions
- Ability to communicate complex technical ideas clearly collaborating effectively with product managers data scientists and engineers across teams
- Growth and mentorship mindset contributing to team learning and helping raise the bar for modeling quality experimentation and reliability
- Commitment to responsible and inclusive personalization ensuring our ML systems respect learner privacy fairness and diverse goals
Bonus points if you have:
- Publications or open-source contributions in RecSys search or ranking
- Familiarity with reinforcement learning for recommendations or contextual bandits
- Experience with hybrid RecSys systems blending collaborative filtering content understanding and LLM-based reasoning
- Prior work in consumer or EdTech applications with personalization at scale
Compensation Benefits & Perks:
- Quizlet is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees. Salary transparency helps to mitigate unfair hiring practices when it comes to discrimination and pay gaps. Total compensation for this role is market competitive including a starting base salary of $209920 - $285000 depending on location and experience as well as company stock options
- 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
Why Join Quizlet
Massive reach: 60M users 1B interactions per week
Cutting-edge tech: Generative AI adaptive learning cognitive science
Strong momentum: Top-tier investors sustainable business real traction
Mission-first: Work that makes a difference in peoples lives
Inclusive culture: Committed to equity diversity and belonging
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 were excited about passionate people joining our teameven if you dont 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.
Quizlets success as an online learning community depends on a strong commitment to diversity equity and inclusion.
As an equal opportunity employer and a tech company committed to societal change we welcome 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!
To All Recruiters and Placement Agencies:
At this time Quizlet does not accept unsolicited agency resumes and/or profiles.
Please do not forward unsolicited agency resumes to our website or to any Quizlet employee. Quizlet will not pay fees to any third-party agency or firm nor will it be responsible for any agency fees associated with unsolicited resumes. All unsolicited resumes received will be considered the property of Quizlet.
#LI-FT
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.
Required Experience:
Staff IC
Key Skills
- Computer Science
- Docker
- Kubernetes
- Python
- VMware
- C/C++
- Go
- System Architecture
- gRPC
- OS Kernels
- Perl
- Distributed Systems
About Company
Quizlet makes simple learning tools that let you study anything. Start learning today with flashcards, games and learning tools — all for free.
