Senior Staff Machine Learning Engineer, Personalization & Recommendations

In this role, you will:

• Work closely with other senior leaders to define and drive the long-term technical vision for personalization and recommendations across multiple Quizlet surfaces, ensuring alignment between modeling strategy, platform capabilities, and product roadmaps
• Communicate complex modeling trade-offs and recommendations to diverse audiences (from senior leadership to cross-functional partners) influencing decisions through clear reasoning, data, and empathy
• Architect and build large-scale personalization models across candidate retrieval, ranking, and post-ranking layers, leveraging user embeddings, contextual signals, and content features to power adaptive learning experiences
• Develop scalable retrieval and serving systems using modern architectures such as Two-Tower, deep ranking, and ANN-based vector search for real-time personalization at global scale
• Lead model training, evaluation, and deployment pipelines for retrieval and ranking systems, ensuring training-serving consistency, reliability, and robust monitoring
• Partner closely with Product and Data Science to translate learning objectives (e.g., engagement, retention, and mastery) into measurable modeling goals and experimentation frameworks
• Advance evaluation methodologies by refining offline metrics (e.g., NDCG, CTR, calibration) and online A/B testing to rigorously measure learner impact and model performance
• Collaborate with platform and infrastructure teams to optimize distributed training, inference latency, and cost-efficient serving in production environments
• Stay at the forefront of personalization and RecSys research, bringing relevant advances from top conferences (KDD, WSDM, SIGIR, RecSys, NeurIPS) into applied production systems
• Mentor and coach engineers and applied scientists, fostering technical excellence, reproducibility, and responsible AI practices across the organization
• Champion a culture of collaboration, inclusivity, and experimentation, helping elevate Quizlet’s AI craft and ensuring personalization systems serve learners equitably and effectively

What you bring to the table:

• 12+ years of experience in applied machine learning or ML-heavy engineering, with deep expertise in personalization, ranking, or recommendation systems
• Proven ability to shape technical direction across multiple teams or disciplines, balancing long-term architectural vision with near-term product and business priorities
• Exceptional communication and storytelling skills — able to distill complex technical concepts into clear narratives for executives, product partners, and non-technical audiences
• Demonstrated leadership through influence, guiding teams through ambiguity, aligning stakeholders around measurable goals, and ensuring accountability for impact
• Experience mentoring senior engineers and applied scientists, leading technical working groups, and driving cross-team innovation and standardization
• Track record of measurable impact, improving key online metrics such as CTR, retention, and engagement through recommender, ranking, or search systems in production
• Deep technical understanding of modern retrieval and ranking architectures (e.g., Two-Tower, deep cross networks, GNNs, MMoE, Transformers) and multi-stage RecSys pipelines.
• 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
• Experience with large-scale embedding models and vector search systems (FAISS, ScaNN, or similar), including training, serving, and optimization at scale
• Expertise in experimentation and evaluation, connecting offline metrics (AUC, NDCG, calibration) with online A/B results to drive confident, data-informed decisions
• Commitment to collaboration and inclusion, fostering a culture that values diverse perspectives, constructive debate, and shared ownership of results

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 $242,240 - $$344,000, 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