ML Force Field Engineer for Materials Discovery — Equity

CuspAI; Amsterdam; Hybrid; EUR 70,000 - 90,000; Full time

Benefits offered by this job

28 days holiday

Gold Standard parental leave

Professional development budget

Equity in CuspAI

Job summary

CuspAI in Amsterdam is seeking a Machine Learning Research Engineer to develop next-generation computational methods for molecular simulations. You will help shape simulation infrastructure, train machine learning force fields, and collaborate closely with computational chemists. Ideal candidates will have a PhD in a relevant quantitative field and demonstrate strong coding and distributed machine learning experience. CuspAI promotes a diverse and inclusive workplace with competitive salaries and comprehensive benefits.

Qualifications

• Demonstrated technical excellence in building performant systems.
• Exceptional coding skills and strong command of software engineering.
• Genuine interest in AI applications in materials science.

Responsibilities

• Train and distill machine learning force fields.
• Integrate models into high-performance simulators.
• Collaborate with computational chemists for data validation.

Skills

Machine learning force fields

Distributed machine learning systems

Coding skills

Software engineering practices

Computational methods

Data generation

Education

PhD in Computer Science, Physics, or relevant field

Tools

Ray

Kubernetes

Job description

CuspAI in Amsterdam is seeking a Machine Learning Research Engineer to develop next-generation computational methods for molecular simulations. You will help shape simulation infrastructure, train machine learning force fields, and collaborate closely with computational chemists. Ideal candidates will have a PhD in a relevant quantitative field and demonstrate strong coding and distributed machine learning experience. CuspAI promotes a diverse and inclusive workplace with competitive salaries and comprehensive benefits.