Applied AI Engineer, Learning Intelligence
Core
Building the intelligence layer for learner growth by owning the skill and concept graph, inferring skill gaps from behavioral signals, and translating inferences into personalized recommendations and dynamic learning paths.
Role type
Senior Applied AI Engineer (Learning Intelligence & Recommendation Systems)
Builds
Skill/concept graphs, ML models for skill inference, and recommendation systems for learning paths
Domain
EdTech / Machine Learning / Knowledge Graphs
Deliverable
production ML models | product features
Required skills
Applied ML, knowledge graphs, graph databases, ontology design, LLM APIs, prompt engineering, Python, production-grade application architecture, model evaluation, context engineering
Preferred skills
Agentic workflows, large-scale deployment, frontend collaboration
Technologies
Python, LLM APIs, Graph Databases, Retrieval frameworks
Responsibilities
Design and maintain a skill and concept graph mapping relationships between skills, roles, and content; Develop ML models to infer learner skill levels from usage patterns and assessments; Build and iterate on recommendation systems for learning paths; Partner with frontend engineers to ensure AI outputs are explainable and reliable; Define explainability standards for model outputs; Monitor model performance and own the evaluation framework
Seniority
Senior, hands-on IC