Description
We are building the intelligence layer that powers how learners grow. This role sits at the intersection of machine learning, knowledge representation, and product engineering. You will own the skill and concept graph that defines what learners know and can do, infer skill gaps from behavioural and profile signals, and translate those inferences into personalised recommendations and dynamic learning that guide each learner to their next best step. You will also be the bridge between our AI capabilities and the engineers building our frontend, making sure AI-driven features ship in a way that is explainable, reliable, and production-ready.
What You Will Do
- Design, build, and maintain a skill and concept graph that maps relationships between skills, roles, domains, and learning content
- Develop ML models that infer learner skill levels from usage patterns, work output, assessments, and profile data
- Build and iterate on recommendation systems that surface the next best module, suggest learning paths, and generate content dynamically
- Partner with frontend engineers to ensure AI outputs are consumed correctly, surfaced with appropriate context
- Define explainability standards for model outputs so users and stakeholders understand why a recommendation was made
- Collaborate with product and content teams to validate recommendation quality and close feedback loops
- Monitor model performance in production and own the evaluation framework for recommendation quality
What We Are Looking For
- 5+ years of experience in applied ML or data science, with production recommendation or personalisation systems in your background
- Hands-on experience with knowledge graphs, graph databases, or ontology design
- Experience with LLM APIs and prompt engineering for generative features
- Hands-on history of shipping LLM-based systems to production, including large-scale deployment, evaluation frameworks, and agentic workflows
- Advanced Python proficiency and experience architecting robust, production-grade applications
- Deep familiarity with the modern AI stack, from retrieval and agent frameworks to complex prompt engineering, model evaluation, and context engineering
- A high degree of intellectual curiosity and the ability to find elegant, straightforward solutions
- Exceptional communication skills, with the ability to translate technical logic for varied stakeholders
Pay Range Transparency
The pay range for this role is: Zone 1 Pay Range $139,000-$191,050 USD Zone 2 Pay Range $125,000-$171,950 USD Zone 3 Pay Range $118,100-$162,350 USD Zone 4 Pay Range $111,200-$152,900 USD
Benefits
At Databricks, we strive to provide comprehensive benefits and perks that meet the needs of all of our employees.