Requirements

• Experience building and maintaining training and inference infrastructure, with an understanding of what it takes to move from concept to production
• A strong mathematical background; Good candidates will be excited about things like optimisation theory, regularisation techniques, linear algebra and the like
• A passion for keeping up with the state of the art, whether that means diving into academic papers, experimenting with the latest hardware or reading the source of a new machine learning package
• A proven ability to create and maintain an organised research codebase that produces robust, reproducible results while maintaining ease of use
• Expertise wrangling an ML framework – we're fans of PyTorch, but we'd also love to learn what you know about Jax, TensorFlow or others
• An inventive approach and the willingness to ask hard questions about whether we're taking the right approaches and using the right tools
• Fluency in English required