SeniorStaff Applied AI Engineer
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Job Location:
San Francisco, CA - USA
Monthly Salary:
$ 183000 - 285000
Posted on:
27 days 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 (Applied AI):
Our mission is to invent and deploy the next generation of intelligent personalized and adaptive learning experiences. Were consolidating AI efforts across the company into a unified portfolio and are accountable for a disproportionate share of Quizlets growth and product differentiation. Youll partner closely with Product Data Science and the AI & Data Platform to deliver an AIdriven learning coach thats recognized as bestinclass.
About the Role:
As an Applied AI Engineer you will be working at the forefront of our AI strategy shaping Quizlets AI develop in one of the two complementary domains:
Personalization & Ranking retrieval and ranking systems that match learners with the right content experiences and monetization moments across surfaces (search feed notifications ads).
Generative AI & Agentic Systems LLMpowered tutoring content understanding/synthesis and tools that boost learner outcomes and creator productivity.
You will work on a variety of models and modeling systems (from TwoTower retrieval and multitask rankers to RAG/LLM pipelines) ensure robust evaluation and responsible deployment
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 facilitates increased work efficiency team partnership and supports growth as an employee and organization.
In this role you will:
- Contribute to the technical roadmap for applied AI across personalization ranking search recommendations and GenAI/LLM systems; help connect modeling work to business metrics (engaged learners conversion retention revenue)
- Build components of endtoend ML systems: candidate sourcing embedding platforms & ANN retrieval multistage ranking (early/late) and value modeling with guardrails for fairness and integrity
- Implement LLMbased features: build RAG pipelines apply instruction/preferencetuning techniques (e.g. SFT/DPO) optimize prompts and improve latency/costaware inference; contribute to offline evals humanintheloop and online success metrics
- Help develop Learner 360 representations by working with behavior signals explicit inputs and conversational context to create robust embeddings reused across surfaces
- Support evaluation infrastructure: contribute to the eval harness for both ranking and generative systems (offline metrics like NDCG/AUC/BLEU/BERTScore; quality/safety scorecards) and help close the loop with online A/B experiments
- Ship reliable systems at scale: ensure trainingserving consistency implement drift detection follow canarying/rollback protocols participate in oncall rotation for model services and maintain strong CI/CD for features & models
- Collaborate with and learn from senior ML/SWE teammates; write highquality code and follow best practices for experimentation rigor and reproducibility
- Work closely with Product Design Legal and Data Science on objectives tradeoffs and responsible AI practices
- Stay current with ML research (RecSys LLMs multimodal) and propose new methods that could improve learner outcomes
What you bring to the table:
- 5-8 years of industry experience in applied ML/AI or MLheavy software engineering
- BS/MS in CS ML or related quantitative field (or equivalent experience)
- Experience building ranking/personalization or search systems (retrieval TwoTower/dual encoders multitask rankers) and contributing to online metric improvements (e.g. CTR session depth retention)
- Handson experience with LLM/GenAI systems: data curation finetuning (SFT/PEFT preference optimization) prompt engineering evaluation and productionization considerations (latency/cost/safety)
- Strong skills in Python/PyTorch data and feature engineering distributed training/inference on GPUs and familiarity with modern MLOps (model registry feature stores monitoring drift)
- Solid experiment design (offline/online) metrics literacy and ability to translate product goals into modeling solutions
- Strong collaboration skills and eagerness to learn from senior engineers; some experience mentoring junior teammates is a plus
Bonus points if you have:
- EdTech or consumer mobile experience; conversational tutoring or learning scienceinformed modeling
- Publications/opensource with RecSys/LLMs (e.g. RecSys KDD NeurIPS ICLR ACL) or contributions to safety/guardrails tooling
- Experience building on a modern MLOps stack (feature mgmt orchestration streaming online inference 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 $183000 - $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.
