Diffractive

<h3>What We're Looking For</h3>We are looking for a Research Scientist to develop new methods in modelling, reasoning, and experiment automation that power our AI-driven material discovery engine. You will own the research direction for problems in this space: designing experiments, evaluating new approaches, and working with engineers to scale what works onto real materials science problems.You will be joining a small, highly ambitious team of world-renowned engineers, AI researchers, and materials scientists. We move fast and value people who are energised by that.This is a role for someone who has a deep understanding of ML research, is excited about pushing the boundaries of what models can do in scientific domains, and wants to make a meaningful contribution to material science.<h3>What You'll Do</h3><ul><li>Formulate and prototype novel machine learning architectures (e.g., foundation models, GNNs, generative models) tailored specifically to the complexities of materials science and chemistry.</li><li>Design active learning and optimization algorithms (such as Bayesian optimization or reinforcement learning) that act as the "brain" of our platform, deciding which physical experiments our autonomous lab should run next.</li><li>Tackle fundamental research challenges in representation learning, specifically devising ways to train effectively on the sparse, noisy, and highly dimensional data generated by real-world physical experiments.</li><li>Collaborate closely with materials scientists and chemists to translate physics, constraints, and scientific intuition into rigorous mathematical models and novel loss functions.</li><li>Drive the research lifecycle from theoretical ideation to proof-of-concept, establishing strong baselines and proving out the viability of new algorithmic approaches before partnering with engineering to scale them.</li><li>Stay at the absolute bleeding edge of machine learning literature, identifying breakthrough techniques from adjacent fields and rapidly adapting them to accelerate our discovery engine.</li></ul><h3>Skill &amp; Qualifications</h3><ul><li>PhD in computer science, machine learning, physics, or a closely related field; experience with scientific or simulation domains strongly preferred.</li><li>Proven track record of developing and evaluating novel ML methods, with a clear understanding of training dynamics and generalisation behaviour.</li><li>Strong Python skills and production-quality research code; experience with PyTorch or an equivalent ML framework.</li><li>Evidence of significant research impact through publications, open-source work, or applied research projects.</li><li>Comfortable working in Linux-based environments, with version control (Git) and HPC or cloud platforms.</li></ul><h3>Nice to Have</h3><ul><li>Experience applying ML in a scientific, simulation, or research computing setting.</li><li>Experience with large-scale or distributed training on GPU clusters.</li><li>Familiarity with scientific data formats and reproducibility practices.</li><li>Contributions to open-source ML or scientific computing packages.</li></ul><h3>Why Join Us</h3>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. We're London-based with a flexible approach to how and where you work. We offer competitive salary, generous equity and benefits. You'll have a real stake in what you build and in the company's overall success.How to ApplyIf you're excited about this role and believe you could thrive in it, we'd encourage you to apply even if you may not align with every part of the job description.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.Hit the apply button below to submit your application. We are looking forward to hearing from you!

Research Scientist, Machine Learning

<h3>What We're Looking For</h3>We are seeking Research Engineers, with strong machine learning experience, to help build the infrastructure, tools, and prototypes that power our AI-driven material discovery engine. You will work across research and engineering, turning new ideas in modelling, reasoning, and experiment automation into robust, scalable systems.You will be joining a small, highly ambitious team of world-renowned engineers, AI researchers, and materials scientists. We move fast and value people who are energised by that.This is a role for someone who is excited about ML at scale, enjoys turning research ideas into working code, and wants to make a meaningful contribution to material science.<h3>What You'll Do</h3><ul><li>Translate cutting-edge ML research and novel architectures into highly performant, scalable implementations for our autonomous discovery platform.</li><li>Design, build, and optimize large-scale distributed training pipelines and inference systems on GPU clusters.</li><li>Profile and optimize model code, identifying and resolving bottlenecks in compute, memory, and data loading to dramatically accelerate our research iteration cycles.</li><li>Develop robust evaluation frameworks and experiment-tracking tooling to bridge the gap between computational model predictions and real-world, physical lab results.</li><li>Curate and architect data pipelines for complex, multimodal scientific data (simulations, structured lab outputs, unstructured text) to feed our training loops.</li><li>Work tightly alongside AI researchers, materials scientists, and software engineers to ensure our models aren't just theoretically sound, but practically deployable in a closed-loop hardware environment.</li></ul><h3>Skill &amp; Qualifications</h3><ul><li>Master's or equivalent experience in Computer Science, Engineering, or a closely related field.</li><li>Deep understanding of machine learning principles and techniques and modern model architectures (e.g. GNNs, Diffusion Models, Transformers)</li><li>Proven hands-on experience building production ML systems, with a clear understanding of training infrastructure, distributed systems, and deployment workflows.</li><li>Strong experience with deep learning frameworks such as PyTorch or JAX Strong programming skills in Python and familiarity with PyTorch or an equivalent ML framework.</li><li>Comfortable taking research ideas (papers, prototypes) and turning them into working, tested code.</li></ul><h3>Nice to Have</h3><ul><li>Experience with large-scale or distributed training and performance optimisation on GPU clusters (multi-GPU/multi-node).</li><li>Experience applying ML systems in a scientific, simulation, or research computing setting.</li><li>Familiarity with scientific data formats and reproducibility practices.</li><li>Experience with technical infrastructure and low-level engineering (e.g. GCP, Kubernetes, Docker)</li></ul><h3>Why Join Us</h3>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. We're London-based with a flexible approach to how and where you work. We offer competitive salary, generous equity and benefits. You'll have a real stake in what you build and in the company's overall success.If you're excited about this role and believe you could thrive in it, we'd encourage you to apply even if you may not align with every part of the job description.How to ApplyIf you're excited about this role and believe you could thrive in it, we'd encourage you to apply even if you may not align with every part of the job description.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.Hit the apply button below to submit your application. We are looking forward to hearing from you!

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Research Scientist, Machine Learning

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