Compiler Engineer

Role: Senior Compiler Engineer

About Tensordyne

Artificial intelligence (AI) is transforming our world. It can perform cognitive functions that previously only humans could do, such as perceiving interactions across different modalities and environments - with the ability to quickly learn and then solve complex problems. Tensordyne is an AI system solution company that builds very high-performance, low-power generative AI inference systems. Our mission, through the creation of custom silicon, hardware and software, is to enable multimodal Generative AI inference acceleration at scale, with safe, sustainable, high-performance systems for our hyperscaler and neocloud data center customers. We are at the leading edge of advancing the latest research and product improvements for generative Al inference solutions that will make Al even more advantageous for compelling new generative AI applications. Tensordyne is a well funded, fast-paced startup company with headquarters in both Sunnyvale, CA, and Munich, Germany. We also have many talented team members working remotely across North America and Europe. We take care of our people and their families with comprehensive benefits, competitive compensation, flexible spending options, and recognition programs, because building category-defining technology starts with a healthy, supported team. Come join us as we shape the future of multimodal generative artificial intelligence!

About the Role

The compiler decides whether our inference silicon runs at 30% utilization or 90% or more. That's the job. Together with our team, you'll build the backend that turns AI workloads into microcode for Tensordyne hardware - Napier today and the silicon that follows. This is a clean-slate compiler effort targeting a genuinely unusual architecture. You'll have the opportunity to work on fundamental parts of the compiler.

The users are changing, too. Increasingly, model mapping and optimization will be done by agents as well as engineers. A compiler designed primarily for humans tends to optimize for escape hatches and manual control. A compiler designed to work effectively with agents needs transparent cost models, structured feedback, machine-readable diagnostics, and fast closed-loop iteration. We need both in the same stack and very few teams are building for this interaction today.

What You'll Do

• Contribute to backend compilation end to end: lowering, instruction scheduling, register and resource allocation, and microcode generation.
• Consider the memory hierarchy: SRAM residency, HBM traffic, DMA orchestration, layout, rematerialization, and data movement. The goal is simple: keep the machine compute-bound rather than waiting on memory.
• Develop tiling, fusion, and software-pipelining strategies that close the gap between theoretical and achieved throughput.