Grafton Sciences ยท 1 day ago
Senior Ontology Engineering Lead
San Francisco, CA
Full-time
Onsite
Senior Level, Lead/StaffGrafton Sciences is building AI systems with general physical ability, aiming to push the frontier of physical AI. They are seeking a Senior Ontology Engineering Lead to design and implement semantic structures that organize knowledge across complex workflows and autonomous systems.
Machine LearningRobotics
Responsibilities
Design and maintain ontologies and knowledge graph schemas that represent entities, relations, events, and processes across complex domains
Implement graph-based knowledge systems (property graphs, RDF/OWL, or hybrid approaches) that support querying, inference, and evolution over time
Define semantic constraints, typing systems, and validation rules to ensure consistency, correctness, and interpretability of knowledge
Build ingestion and update mechanisms that integrate heterogeneous data sources into unified semantic representations
Collaborate with agents, ML, and systems teams to ensure knowledge representations are usable by planners, reasoning engines, and learning systems
Develop tooling for ontology evolution, versioning, alignment, and impact analysis as schemas and domains change
Support reasoning and decision pipelines by enabling symbolic queries, rule-based inference, or hybrid neuro-symbolic integration
Act as a cross-functional technical partner, translating domain knowledge into formal structures and ensuring semantic layers scale with system complexity
Qualification
Required
Strong background in ontology engineering, knowledge representation, semantic modeling, or knowledge graphs
Experience designing and implementing ontologies or schemas for complex domains (e.g., processes, workflows, scientific data, enterprise systems)
Familiarity with graph data models and technologies (e.g., RDF/OWL, SPARQL, property graphs, Neo4j, TigerGraph, or similar)
Understanding of computational logic, typing systems, constraints, or rule-based inference
Comfort working alongside ML and data systems, and bridging symbolic semantics with statistical or learned components
Experience designing abstractions that support large-scale, evolving, real-time knowledge updates
High-agency engineer who enjoys defining structure in ambiguous domains and building semantic systems from first principles
MS degree (or equivalent) required
Preferred
PhD preferred
Benefits
Meaningful equity
Benefits
Company
Grafton Sciences
Building systems of general physical ability to enable superintelligence
Founded in 2024
11-50 employees
H1B Sponsorship
Grafton Sciences has a track record of offering H1B sponsorships. Please note that this does not
guarantee sponsorship for this specific role. Below presents additional info for your
reference. (Data Powered by US Department of Labor)
Distribution of Different Job Fields Receiving Sponsorship
Represents job field similar to this job
Trends of Total Sponsorships
2025 (2)
Funding
Current Stage
Early StageCompany data provided by crunchbase