Research Scientist/Engineer, GNNs
remotemid
via Ashby
About this role
What We’re Looking For
We are looking for a Machine Learning Engineer to take ownership of training and fine-tuning machine-learning interatomic potentials (MLIPs) for magnetic and structural materials. You will work at the intersection of modern ML and first-principles simulation, leveraging our DFT datasets to feed our models and pushing MLIP architectures into new physical regimes; particularly spin-dependent interactions.
You will be joining a small, highly ambitious team of world-class materials scientists, engineers, and AI researchers. We move fast and value people who are energised by that.
This is a role for someone who has a deep understanding of MLIPs, is excited about pushing the boundaries of machine learning, and make a meaningful contribution to material science.…
What we'd score you on
reqspace match rubricFive dimensions, recruiter-grade. Upload your resume and we'll generate a written explanation of where you fit and where the gaps are.
1
Skills match
For this role: python, c++, pytorch, jax
2
Level fit
This role is mid-level. We check your trajectory against it.
3
Domain experience
Your work in the role's domain matters more than your years total. We weight recent and direct experience.
4
Recency
A skill you used last quarter weighs more than one from five years ago. We grade on recency, not lifetime.
5
Location fit
This role is remote-eligible — we factor in your stated location and time-zone overlap.
Score yourself on this role.
Free · no card · written explanation included
Skills in this role
Pulled from the job description. These are the keywords we'll weight when scoring your fit.
pythonc++pytorchjax