Software Architect - AI Systems & Hardware Co-Design
We're working with a well-backed, seed-stage company operating at the frontier of AI and semiconductor design. Our client is solving a genuinely novel infrastructure problem in the AI space. The founding team has deep roots at top-tier hardware companies and a strong research pedigree in AI-aided chip design.
This is a ground-floor opportunity - you'd be one of a small number of technical hires shaping the direction of the company.
The Role
You'll sit at the intersection of frontier AI software and specialized silicon - mapping complex model workloads to custom hardware architectures and defining how the two co-evolve. Your work will directly impact the efficiency and scalability of next-generation AI systems.
What You'll Be Doing
- Architecting how LLM and multimodal workloads map to specialized AI accelerator hardware.
- Optimizing inference kernels - attention mechanisms (FlashAttention), KV cache management, quantization (INT4), and sparse tensor compression.
- Defining hardware-software interfaces with a focus on energy efficiency and low-power edge performance.
- Conducting PPA trade-off analysis across compute density, memory bandwidth, and on-chip SRAM.
- Contributing to AI-aided design research to accelerate the architectural design loop.
What They're Looking For
- 5+ years in AI accelerator software-hardware co-design.
- Hands-on experience with NVDLA, Tensor Cores, or custom NPUs - real silicon, not simulated.
- Strong background in LLM inference optimization on GPUs - attention kernels, memory management, quantization.
- Deep understanding of HBM economics and memory bandwidth constraints in AI infrastructure.
- Master's or PhD in EE or CS preferred - especially with a research focus on AI-aided hardware design.
- Familiarity with emerging architectures such as SSMs (Mamba).
If you're a systems-level engineer who has operated at the boundary of software and silicon - and you want to work on something foundational rather than incremental - APPLY NOW
