Jobs at CuspAI

The Data Engineer will build data pipelines for materials science, ensuring data quality and collaborating with ML researchers while managing large datasets.

Lead technical enablement and scientific advisory for partners adopting CuspAI's platform. Engage computational chemists and materials scientists, run workshops and code-alongs, create advanced developer resources (docs, notebooks, APIs), and drive cross-functional feedback into AI research and product. Support partner discovery sprints and co-author deep-tech content to showcase materials breakthroughs.

Lead global partnership efforts for CuspAI's AI Materials Foundry by building partner frameworks, coordinating cross-cultural operations across Europe, USA, and APAC, managing stakeholder engagement and timelines, and channeling partner feedback into product and research priorities while supporting events, marketing, and PR to accelerate platform adoption.

You will lead the development of internal applications for material discovery, ensuring they are high-quality products through collaboration and iterative design.

Develop intelligent agents for a materials discovery engine, orchestrating scientific workflows and integrating experimental design for sustainability solutions.

As an ML Research Engineer, you will develop computational methods and infrastructure to enhance molecular simulations and machine learning force fields for materials discovery.

3-month engineering internship to distill fast, accurate ML force fields for Monte Carlo (GCMC), integrate them into kUPS, validate against classical force fields, profile and optimize inference in the MC inner loop, curate datasets, and collaborate on benchmarks and publications.