Inference infrastructure Engineer

I'm hiring a Member of Technical Staff, ML Systems to join an early-stage AI infrastructure company building a new memory layer for large-scale inference. The team is developing custom silicon and systems software that give GPUs and other AI accelerators access to a much larger high-bandwidth memory tier, with a particular focus on long-context inference, KV-cache management and reducing the cost of keeping large amounts of model state close to compute. This is a low-level ML systems role working across inference engines, GPU performance and hardware/software co-design rather than application-layer AI.Build and optimise LLM inference systems around distributed and expandable memory Work across KV cache, data movement, GPU kernels and serving performance Help shape the underlying hardware architecture using real workload behaviour The team is particularly interested in engineers with experience around vLLM, SGLang, TensorRT-LLM, LMCache, CUDA or similar inference infrastructure.