Materials Knowledge Architect: Data Models & Pipelines

CuspAI; Greater London; Hybrid; GBP 90,000 - 130,000; Full time

Benefits offered by this job

Equity in CuspAI

Competitive salary

28 days holiday (UK) and public hols

Parental leave

Job summary

CuspAI is building a next-generation data platform for materials discovery. We seek a Materials Knowledge Architect to design data representations, schemas and ingestion pipelines that unify heterogeneous external data into actionable assets for AI-driven discovery.

You will work with AI researchers, chemists and engineers to maximise data quality, scale and interoperability, enabling rapid breakthroughs in materials science.

Qualifications

• PhD in Chemistry, Physics, Materials Science, Computational Chemistry or equivalent experience.

Responsibilities

• Design data models and schemas for chemical, structural and materials property data.
• Lead ingestion of data from partners and build robust pipelines for normalising varied formats.
• Collaborate with researchers and engineers to translate modelling needs into data requirements.
• Ensure data quality, provenance and ML-readiness across ingested datasets.

Skills

Data modeling

Data ingestion

Ontology design

Data curation

Materials data sources

Python

SQL

Pydantic

JSON Schema

pymatgen

Education

PhD in Chemistry/Physics/Materials Science

Tools

Python

SQL

Pydantic

JSON Schema

pymatgen

ASE

Job description

CuspAI is building a next-generation data platform for materials discovery. We seek a Materials Knowledge Architect to design data representations, schemas and ingestion pipelines that unify heterogeneous external data into actionable assets for AI-driven discovery.

You will work with AI researchers, chemists and engineers to maximise data quality, scale and interoperability, enabling rapid breakthroughs in materials science.