Sr. Performance Modeling Architect

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.

Tenstorrent is building cutting-edge processors and systems for AI workloads, bringing together world-class expertise in silicon, systems, and software. We are seeking a CPU Performance Modeling Architect to help shape the next generation of high-performance RISC-V CPUs optimized for AI and high-performance computing applications. This role is ideal for early-career architects with a strong academic background, ideally a PhD, who have experience working on CPU core or mid-core architecture and are passionate about using performance modeling to influence architectural decisions.

This role is hybrid, based out of Santa Clara, CA or Austin, TX.

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 have 1-5 years of industry experience or equivalent research experience in CPU architecture, performance analysis, or microarchitecture development.

• You have a strong foundation in CPU core or mid-core design and understand modern processor pipelines and performance tradeoffs.

• You enjoy combining analytical thinking, software development, and hardware architecture to solve complex performance challenges.

• You are collaborative, curious, and excited to work on building industry-leading AI compute platforms.

What We Need