Brief:

• Designing and developing the software systems that enable us to run machine learning (ML) inference workloads at state of the art latencies and efficiency on FPGA-based hardware accelerators.
• Working throughout the stack to define the ways we program AI accelerators, from co-designing the instruction sets together with the hardware engineering team, to developing the compilers and application APIs to interface the accelerator with ML models and frameworks. 

Responsibilities:

• Programming our bespoke hardware accelerators by writing compilers and DSLs
• Creating tools for debugging, profiling, and optimising programs for our accelerators
• Developing efficient applications and runtime libraries for server CPUs that utilise our accelerators 

Key Requirements:

• PhD or MSc in related field
• Used Rust in production or open source codebases
• Experience with low-level programming languages in general (e.g. Rust, C, C++) or functional programming languages (e.g. Haskell, OCaml, Nix) 3 years of experience working on relevant areas such as performance sensitive- or systems programming, and compiler development