AI Tutoring Dialogue Quality Engineer

About the role

Responsibilities

• Build learning outcome predictors from student interaction and assessment data
• Develop dialogue quality classifiers identifying confusion-inducing response patterns
• Design RLHF-style training signal using learning outcomes as dialogue quality reward
• Create evaluation framework measuring dialogue quality against student learning gains
• Build A/B testing infrastructure for dialogue strategy experiments
• Collaborate with learning science researchers to validate model-based quality signals

Requirements

• 5+ years in NLP engineering with dialogue systems or conversational AI experience
• Experience with RLHF, preference learning, or reward model design
• Strong Python and PyTorch skills with LLM fine-tuning experience
• Ability to work with education domain experts on pedagogy-informed system design
• Interest in education technology and learning outcomes

Benefits

• Fully remote
• Health, dental, and vision
• $4,000 annual learning budget
• Equity package
• Meaningful social impact in education

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