Applied AI Engineer (Learning Intelligence)

TL;DR

Applied AI Engineer (Learning Intelligence): Building the intelligence layer for learner growth by designing skill and concept graphs and inferring skill gaps from behavioral signals with an accent on personalized recommendations and dynamic learning. Focus on designing ML models for skill inference, optimizing recommendation systems, and shipping production-ready LLM-based agentic workflows.

Location: United States

Salary: $111,200 — $191,050 USD (depending on location zone)

Company

Databricks is a data and AI company that provides a Data Intelligence Platform to unify and democratize data, analytics, and AI for over 10,000 organizations worldwide.

What you will do

• Design and maintain a skill and concept graph mapping relationships between skills, roles, domains, and learning content.
• Develop ML models to infer learner skill levels using usage patterns, work output, and profile data.
• Build and iterate on recommendation systems for personalized learning paths and dynamic content generation.
• Partner with frontend engineers to ensure AI outputs are consumed correctly and surfaced with appropriate context.
• Define explainability standards for model outputs to ensure transparency for users and stakeholders.
• Monitor production model performance and own the evaluation framework for recommendation quality.

Requirements

• 5+ years of experience in applied ML or data science, specifically with production recommendation or personalization systems.
• Hands-on experience with knowledge graphs, graph databases, or ontology design.
• Proven history of shipping LLM-based systems to production, including evaluation frameworks and agentic workflows.
• Advanced Python proficiency and experience architecting robust, production-grade applications.
• Deep familiarity with the modern AI stack, including retrieval and agent frameworks and context engineering.
• Must be authorized to work in the United States.

Culture & Benefits

• Comprehensive benefits and perks tailored to the employee's region.
• Strong commitment to diversity, equity, and inclusion in hiring and workplace culture.
• Opportunity to work at a company used by over 50% of the Fortune 500.
• Collaborative environment at the intersection of machine learning and product engineering.