Software Engineer, Metal Runtime (Core Systems)
$100kTenstorrent
Tenstorrent is leading the industry on cutting-edge AI technology, revolutionizing performance expectations, ease of use, and cost efficiency. With AI redefining the computing paradigm, solutions must evolve to unify innovations in software models, compilers, platforms, networking, and semiconductors. Our diverse team of technologists have developed a high performance RISC-V CPU from scratch, and share a passion for AI and a deep desire to build the best AI platform possible. We value collaboration, curiosity, and a commitment to solving hard problems. We are growing our team and looking for contributors of all seniorities. As a Software Engineer on the Metal Runtime team at Tenstorrent, you’ll work on the low-level software that powers our AI accelerators. You’ll build and optimize high-performance runtime systems that execute directly on the hardware, focusing on scheduling, memory movement, and efficient execution across massively parallel processors. We believe runtime systems are a core part of performance: they determine how hardware resources are utilized, how data flows through the system, and how efficiently workloads are executed at scale. If you enjoy pushing performance, working close to the metal, and solving complex systems challenges at the hardware/software boundary, this is your kind of role. This role is hybrid, based out of Santa Clara, CA; Austin, TX; Toronto, ON. We welcome candidates at various experience levels for this role. During the interview process, candidates will be assessed for the appropriate level, and offers will align with that level, which may differ from the one in this posting. Who You Are
- Strong coder in C or C++, and love working close to hardware.
- Comfortable thinking in terms of threads, processors, and memory movement,
- Curious about how runtimes and bare-metal software come together to power AI.
- Collaborative by nature and enjoy solving tough problems with smart people.
- Optimize memory movement and data flow across massively parallel hardware.
- Work closely with hardware teams to maximize performance and efficiency of
- How to design high-performance runtime systems for cutting-edge AI hardware.
- How execution, scheduling, and memory systems interact at scale.
- How to make custom ASICs and co-processors work efficiently across the chip.
- Best practices for debugging complex, performance-critical software.
- How software and hardware co-evolve in a fast-paced AI startup.
$100k
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