AI Compiler Lead; ML Accelerator

About the role

We're building a next-generation low-power AI accelerator (NPU) for physical AI, robotics, drones, and edge devices where latency, power, and memory movement are everything. You'll own the compiler and model-lowering stack from scratch: taking AI models and lowering them onto brand-new silicon as efficiently as the chip allows, working hand in hand with our silicon architects.

This is the most important software hire on the team and a true 0-to-1 build. You'll architect the full stack yourself early on, then hire and lead the compiler team beneath you as we scale over the next year.

What you'll do

• Build the full compiler stack end to end, from model ingestion (graph import, operator lowering, IR) to optimized executable output for our NPU
• Work with silicon architects to schedule memory movement, integrate quantization, and partition graphs for efficiency and lowest latency
• Own graph transformations, quantization integration, code generation, and compiler diagnostics
• Hire and lead the compiler and ML systems team, and serve as technical authority for evaluating future compiler talent

What we're looking for

• 10+ years in industry, 5+ specifically in compiler development for ML accelerators, GPUs, or DSPs
• Hands-on across the full pipeline: graph import, operator lowering, compiler IR, graph transformations, quantization, and graph partitioning
• Real depth building compiler internals, not just using existing tool chains, ideally for custom or novel silicon
• A team lead who still wants to be hands-on, excited to architect and write code, not just manage
• Builder-level familiarity with MLIR, LLVM, TVM, XLA, IREE, or Glow