Sr. Engineer, Ethernet IP

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.

This role sits at the deep-tech intersection of silicon development, low-level firmware, and high-speed networking. You won't just be writing drivers; you’ll be the bridge between our AI silicon and the network. You will work with best-in-class Ethernet IP and in-house designs to architect, enable, and optimize the firmware that powers next-generation AI infrastructure. The role is focused on the hardware-software boundary, spanning silicon bring-up, SerDes/PHY configuration, and performance tuning to ensure seamless, high-performance connectivity across complex, large-scale platforms.

This role is hybrid, based out of Toronto, Canada or Vancouver Canada.

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

• You are passionate about the "first few layers" of the stack. You’d rather debug a link-training state machine than a high-level application.

• You thrive on understanding the inner workings of Ethernet hardware (MAC/PHY/PCS) and how to control it efficiently via bare-metal firmware.

• You enjoy the "detective work" of hardware bring-up, using oscilloscopes or logic analyzers when the software behavior doesn't match the silicon's intent.

• You speak the languages of both the RTL team and the Network Software team, translating hardware constraints into software requirements.

What We Need