At a Glance
- Tasks: Build scalable ML infrastructure and translate research into production-quality systems.
- Company: Exciting AI-native startup reinventing material discovery with cutting-edge technology.
- Benefits: Competitive salary, innovative projects, and the chance to work with world-class researchers.
- Other info: Significant technical ownership and dynamic environment with exceptional career growth.
- Why this job: Join a well-funded company and accelerate scientific discovery in impactful areas.
- Qualifications: Strong ML engineering experience and excellent Python skills with modern architectures.
The predicted salary is between 72000 - 88000 £ per year.
We're partnering with one of Europe's most exciting AI-native startups that's building an autonomous AI platform to fundamentally reinvent how new materials are discovered.
Rather than relying on simulations alone, they're combining cutting-edge machine learning with a high-throughput experimental laboratory, creating a closed-loop system where AI designs new materials, experiments validate them, and real-world results continuously improve the models.
Backed by $60M from leading global investors , they've assembled an exceptional team spanning AI, physics, materials science and engineering, and are now looking for outstanding Machine Learning Research Engineers to help build the infrastructure powering the next generation of AI for Science.
You'll be working on: Building scalable ML infrastructure for frontier AI research Translating novel research into production-quality ML systems Distributed training and inference across large GPU clusters Optimising model performance, training pipelines and experimentation workflows Developing multimodal data pipelines spanning simulations, laboratory data and scientific literature Working alongside world-class AI researchers, engineers and scientists to deploy models into a real-world autonomous experimentation platform We're looking for: Strong Machine Learning Engineering experience Deep knowledge of modern ML architectures (Transformers, GNNs, Diffusion Models, etc.) Excellent Python skills with Py Torch and/or JAX Experience building scalable production ML systems Someone who enjoys turning cutting-edge research into robust, high-performance software Bonus experience: Distributed GPU training (multi-GPU / multi-node) Scientific machine learning or simulation environments Performance optimisation and systems engineering Docker, Kubernetes, GCP or similar infrastructure Scientific computing or research engineering backgrounds Why this opportunity?
This is a chance to join an exceptionally well-funded AI-for-Science company at an early stage and help build technology capable of accelerating scientific discovery in areas that matter globally.
You'll work alongside some of the world's leading researchers on genuinely novel problems, with significant technical ownership from day one.
Research Engineer, Machine Learning employer: Generative
As a Machine Learning Researcher at our London-based AI lab, you'll be part of a dynamic and ambitious team dedicated to solving significant scientific challenges through innovative AI solutions. We foster a collaborative and inclusive work culture that values curiosity and low ego, offering flexible hybrid working arrangements and opportunities for professional growth in a supportive environment. Join us to make a tangible impact from day one, as you contribute to cutting-edge research that accelerates the discovery of commercially valuable materials.
