Job Opportunities API

At Fractile, we’re taking a revolutionary approach to computing to run the world’s largest language models 100x faster than existing systems. Our fast-growing team is working at the cutting edge of the latest AI developments in both hardware and software. Want to get involved? We are looking for Senior ML Compiler Engineers with experience in machine learning compilation to work on the compiler stack for our ground-breaking AI accelerators. You can be based in our Bristol office or London, the choice is yours. Why Fractile:  We're building something that doesn't exist yet. Fractile isn't another AI startup gluing together frameworks.  We are designing a full-stack execution engine: hardware, compiler, runtime, to build the world's largest language models 100 x faster than today's systems.  That ambition forces us to rethink everything from first principles. For compiler engineers, this is a rare moment: the architecture is still being shaped.  The IR, the lowering strategy, the optimisation passes, the execution model - you get to define its future. In this role, you will: Develop the machine learning compiler stack for Fractile’s innovative AI acceleration hardware Enable industry-leading performance of the latest LLMs on Fractile’s accelerators Work with hardware, driver runtime, and ML engineers in a highly collaborative hardware-software co-design methodology It would be great if you have: Proven experience of the development of machine learning compilers using industry standard technologies such as MLIR or TVM Up-to-date knowledge of machine learning techniques and technologies A good understanding of computer architecture and performance optimisation techniques Excellent C/C++ skills and solid experience of industry standard development tools and technologies An creative and innovative mindset, and a willingness to take ownership and drive results in a fast-paced environment Computer Science, Electronic Engineering, Maths, Physics, or related degree and 3+ years of industry experience You may also have: Previous experience in a startup or small team environment