Software Engineer, Metal Runtime (API & Abstractions)

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 design fast, efficient runtime systems that run close to the hardware, and define the host and device APIs that expose these capabilities to the rest of the software stack. We believe APIs are a core part of systems design: they encode hardware semantics, performance tradeoffs, and concurrency models, and they live longer than any single implementation.

If you enjoy pushing performance, working close to the metal, and designing abstractions that make complex systems usable without sacrificing control, 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 enjoy working close to hardware.

• Comfortable thinking in terms of threads, processors, and memory movement.

• Care deeply about API design, abstraction boundaries, and developer experience in low-level systems.

• Experienced (or interested in) designing libraries or interfaces used by other engineers.

• Think about long-term maintainability, usability, and clarity when designing systems.