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Silicon Software Lead (Software Lead)
Normal Computing · New York, United States
About The Role
Join Normal Computing, a groundbreaking company that is revolutionizing the way we think about silicon and AI inference. As the Silicon Software Lead, you will lead the team that builds the software stack for our innovative chip, working closely with hardware architects and driving the development of the runtime, kernels, drivers, and debugging tools. This is a unique opportunity to shape the future of computing and make a real impact in the field of AI.
- Lead and grow the silicon software team, overseeing the development of the compiler, runtime, kernels, drivers, and hardware abstraction layer.
- Own the architecture of the software stack, ensuring it is designed to work seamlessly with the hardware and meets the needs of real inference workloads.
- Set the silicon software roadmap, define milestones against the hardware program, and hire the engineers who deliver it.
- Track record of hiring and developing strong systems engineers
- Experience with compiler frameworks such as MLIR or LLVM, or with inference runtimes and kernel development
- Deep understanding of ML inference workloads and the constraints that shape their execution on hardware
- Comfort building software for hardware that is still evolving, from simulation through bring-up
- Experience leading engineers as a technical lead or manager while staying hands-on in design and code
- Strong systems programming skills in C++, Rust, or equivalent, with fluency in Python
- Substantial experience building software stacks for accelerators or non-standard hardware targets: compilers, runtimes, kernels, or drivers
- Experience taking an accelerator software stack from zero to production at a startup or new hardware program
- Experience with in-memory compute, processing-in-memory, or analog hardware interfaces
- Contributions to open-source compiler or runtime infrastructure
- Experience with hardware-software co-design where software insights shaped ISA or architecture decisions
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