Performance Architect, AI HW

Join to apply for the Performance Architect, AI HW role at Tenstorrent Tenstorrent is leading the industry on cutting‑edge AI technology, revolutionizing performance expectations, ease of use, and cost efficiency. We value collaboration, curiosity, and a commitment to solving hard problems. We are growing our team and looking for contributors of all seniorities. Overview The Tensix team is building the high‑performance compute fabric that powers Tenstorrent’s AI and ML workloads. As an AI Performance Architect, you will model, analyze, and optimize how real AI workloads run on the Tensix architecture, shaping future hardware features and ensuring every design decision delivers measurable performance gains. This role connects architecture, software, and RTL to push the limits of efficiency and scalability across next‑generation AI systems. This role is hybrid, based out of Toronto, ON; Austin, TX; or remote. We welcome candidates at various experience levels; during the interview process, candidates will be assessed for the appropriate level. Who You Are Deeply analytical engineer with strong intuition for AI workload behavior and system‑level performance bottlenecks. Experienced in C++ and Python for simulation, modeling, and performance analysis across heterogeneous compute systems. Adept at bridging software and hardware teams—translating deep learning workloads into architectural insight and measurable design tradeoffs. Curious, data‑driven, and comfortable pushing the limits of efficiency, scalability, and accuracy in high‑performance AI systems. What We Need Benchmark and analyze complex AI workloads across single and multi‑node hardware configurations to guide next‑gen architecture. Develop and maintain performance models, simulators, and micro‑benchmark suites to drive feature evaluation and design optimization. Conduct detailed PPA (Performance, Power, Area) studies to assess design tradeoffs and inform hardware‑software co‑design decisions. Collaborate closely with RTL, Compiler, and Runtime teams to instrument and correlate performance models with silicon results. What You’ll Learn Advanced modeling techniques for large‑scale AI systems, including multi‑chip and distributed performance analysis. How architectural choices propagate through the software stack—from compiler and runtime layers down to custom AI accelerators. Emerging deep learning trends and their impact on compute architecture design and performance tuning. How to define and validate performance features that directly translate to measurable gains across real‑world AI workloads. Compensation Compensation for all engineers at Tenstorrent ranges from $100k – $500k including base and variable compensation targets. Experience, skills, education, background and location all impact the actual offer made. Equal Opportunity Tenstorrent offers a highly competitive compensation package and benefits, and we are an equal opportunity employer. This offer of employment is contingent upon the applicant being eligible to access U.S. export‑controlled technology. Due to U.S. export laws, including those codified in the U.S. Export Administration Regulations (EAR), the Company is required to ensure compliance with these laws when transferring technology to nationals of certain countries (such as EAR Country Groups D:1, E1, and E2). These requirements apply to persons located in the U.S. and all countries outside the U.S. As the position offered will have direct and/or indirect access to information, systems, or technologies subject to these laws, the offer may be contingent upon your citizenship/permanent residency status or ability to obtain prior license approval from the U.S. Commerce Department or applicable federal agency. If employment is not possible due to U.S. export laws, any offer of employment will be rescinded. #J-18808-Ljbffr