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About the Role
We are seeking a Machine Learning Engineer to train and fine-tune machine-learning interatomic potentials (MLIPs) for magnetic and structural materials. This role involves working at the intersection of ML and simulation, leveraging DFT datasets to advance MLIP architectures, particularly for spin-dependent interactions. You will join a small, ambitious team of experts and contribute meaningfully to materials science.
Responsibilities
- Pre-train and fine-tune MLIPs for solid-state systems, focusing on magnetic materials.
- Design and build DFT training-set workflows, including active learning loops, convergence testing, and data curation.
- Extend existing MLIP architectures to capture spin-lattice interactions.
- Build and maintain automated, reproducible workflows for dataset generation and model iteration.
- Work directly with materials scientists to translate physical intuition into training objectives and dataset design.
Requirements
- PhD in physics, chemistry, materials science, or a closely related field; solid-state focus strongly preferred.
- Proven hands-on experience training or fine-tuning MLIPs, with a clear understanding of training dynamics, loss landscapes, and generalization behaviour.
- Experience working with DFT-generated training sets and experimental material science data.
- Strong Python skills and production-quality research code.
- Experience with PyTorch or JAX.
- Familiarity with atomistic simulation packages (VASP, Quantum Espresso, LAMMPS, or similar).
- Evidence of significant research impact through publications in ML for atomistic modelling, computational materials science, or related technical disciplines.
Skills
- Python
- PyTorch
- JAX
- C/C++
- Rust
- AiiDA
- FireWorks
- VASP
- Quantum Espresso
- LAMMPS
- MLIPs
- DFT
- Active learning
- Long-range or equivariant message-passing architectures
- Spin-polarised or non-collinear DFT calculations
Location
- London-based
Work Type
- Flexible approach to how and where you work
Experience Level
- PhD
Education Level
- PhD
Salary/Compensations
- Competitive salary
Benefits
- Generous equity
- Benefits
About the Company
- Diffractive is building the AI Material Scientist that autonomously learns from real-world experimentation to push the boundaries of scientific discovery.
- We're early, moving fast, and working on problems that genuinely matter.
- You'll join a small, high-calibre team where your work has real impact from day one.
Equal Opportunity
- Diffractive is an equal opportunities employer.
- We are committed to creating an inclusive environment for all employees and welcome applications from people of all backgrounds, experiences, and identities.
- If you require any adjustments or accommodations at any point during the interview process please let us know - we will be happy to help.