AI Materials Knowledge Architect

CuspAI; Cambridge; Hybrid; GBP 90,000 - 130,000; Full time

Benefits offered by this job

Equity in CuspAI

28 days annual leave (UK)

Professional development budget

Hybrid work model

Job summary

CuspAI is seeking a Materials Knowledge Architect to design data representations and ingestion pipelines for heterogeneous scientific data. You will own how data is represented, modelled and brought into CuspAI, ensuring quality at scale to fuel materials discovery.

You will work closely with AI experts and materials researchers to build interoperable data assets and robust data pipelines from multiple external sources, enabling ML-ready datasets for cutting-edge projects.

Qualifications

• PhD or equivalent with strong data modelling experience in scientific domains.
• Experience ingesting and harmonising data from multiple external sources.
• Expertise in data representation, ontologies and interoperable assets.
• Strong collaboration skills with external partners and cross-functional teams.

Responsibilities

• Design data models and schemas for complex scientific data.
• Lead ingestion pipelines, normalisation and reconciliation of data.
• Collaborate with researchers and engineers to deliver ML-ready datasets.

Skills

Data modeling

Data schemas

Data quality

Python

SQL

communication

Education

PhD in Chemistry/Physics/Materials Science or related

Tools

JSON Schema

Pydantic

pymatgen

ASE

Pandas/Polars

Job description

CuspAI is seeking a Materials Knowledge Architect to design data representations and ingestion pipelines for heterogeneous scientific data. You will own how data is represented, modelled and brought into CuspAI, ensuring quality at scale to fuel materials discovery.

You will work closely with AI experts and materials researchers to build interoperable data assets and robust data pipelines from multiple external sources, enabling ML-ready datasets for cutting-edge projects.