Jobs at CuspAI

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.

Lead the technical strategy and project execution for CuspAI in Singapore, managing local teams and translating commercial needs into technical solutions. Drive growth and partnerships while ensuring alignment with global strategies.

Apply computational chemistry and materials modeling to scope and run discovery campaigns: build and deploy ML and simulation workflows (MD, DFT, electronic-structure), interpret results for customers, collaborate with R&D/product, and represent technical work externally.

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

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.