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Faculty · 1 month ago

Learning Engineer

London - Hybrid

Full-time

Hybrid

Mid Level

Faculty is a company that transforms organizational performance through human-centric AI. As a Learning Engineer, you will design the learning logic for innovative education products, ensuring they are effective at scale while bridging the gap between academic research and real-world application.

Artificial Intelligence (AI)B2BInformation TechnologyMachine LearningSaaSSoftware

Growth Opportunities

Responsibilities

Defining clear learning goals and skill models, then breaking them down into scaffolded tasks, feedback loops, and adaptivity logic for the product team

Identifying what we need to measure (e.g., mastery, engagement, retention) and working with data teams to ensure our products track the right learning behaviors

Leading user testing and formative studies to test early prototypes, and collaborating with data scientists to review performance data once live

Acting as the voice of "Learning Science" within product teams—translating pedagogical principles into clear specifications for UX designers ,data scientists and engineers

Contributing to Faculty’s Learning Engineering Playbook—creating checklists, design patterns, and templates to support consistency across projects

Supporting teams in applying learning science best practices through collaborative design workshops and guidance

Qualification

Learning sciencesInstructional designEducational psychologyData analysisUser experience designExperimentationClear communicationCollaboration

Required

You have a strong background in learning sciences, instructional design, educational psychology, or a related field

You understand how to balance learning principles with real product constraints (UX feasibility, technical constraints, timelines)

You have a portfolio of digital learning experiences and understand the constraints and opportunities of building software products (e.g., LMS, Apps, EdTech tools)

You are comfortable working with data. You understand how to define success metrics and can interpret reports to make evidence-based design decisions

You've collaborated closely with UX / UXR teams and can translate learning logic into user flows, prototypes, and interaction patterns

You are comfortable with experimentation (A/B tests, early prototype testing, formative evaluation)

You are a clear communicator who can translate academic concepts (like 'cognitive load' or 'zone of proximal development') into practical, actionable tickets for engineering and design teams

This is not a content-creation or e-learning production role. We are looking for someone with experience designing learning systems, not just courses