Machine Learning Research Engineer / Scientist

Role Overview

We are seeking Machine Learning Research Engineers / Scientists to join our team working on groundbreaking physics foundation models. The successful candidate will develop, train and deploy to production large-scale AI foundation models to advance the state-of-the-art in weather prediction and large-scale physical simulations more generally.

What You'll Do

• Architect and implement innovative ML models for complex spatiotemporal data analysis.
• Lead end-to-end development of large-scale AI systems, from research to production.
• Drive the optimisation of training and inference pipelines for maximum performance.
• Conduct validation experiments and performance analysis.
• Spearhead long-term research initiatives with significant real-world impact.
• Collaborate with world-class researchers and engineers.
  
  

We expect you to have

• Proven track record in developing and deploying deep learning models.
• Advanced proficiency in Python and modern ML frameworks (PyTorch, TensorFlow, Jax).
• Demonstrated experience with distributed training systems and large-scale data pipelines.
• Strong software engineering practices and system design principles.
• Excellent problem-solving and analytical skills.
• Outstanding communication and collaboration abilities.
  
  

Nice to have

• MSc or PhD in Artificial Intelligence, Computer Science, or related technical field.
• Published research in prestigious AI conferences/journals (NeurIPS, ICML, etc.).
• Hands-on experience with one or several of the following: transformers, diffusion models, self-supervised learning, foundation model training/fine-tuning.
  
  

Join us in pushing the boundaries of physics foundation models!