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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. At Tenstorrent, we believe the future of computing must be open, which is why our interns don’t just watch from the sidelines - they help build the core of it. We provide a "code-to-career" pipeline where students collaborate with industry experts to solve high-stakes problems in RISC-V and AI hardware-software co-design. By joining us, you are taking an internship to democratize high-performance computers that are accessible to everyone. As a CPU Performance Architect Intern at Tenstorrent, you will join a team of world-class CPU designers and performance architects to shape the future of high-performance computing. You will research emerging CPU workloads, analyze their impact on next-generation CPUs, accelerators, and build innovative solutions that maximize hardware performance.     This role is on-site, based in our Santa Clara, CA office. We may also consider remote candidates  on a case-by-case basis .       Who You Are   Currently pursuing a Ph.D. in Computer Architecture, Parallel Computing Artificial Intelligence/ Machine Learning, or a related field, with a strong publication record. Strong foundation in computer organization, computer architecture, parallel computation and digital logic design.   Hands-on with Linux, performance and power profiling tools, Silicon PMU profiling, and hardware performance counters.   Proficient in Shell scripting, Python, and C++, with experience in PyTorch, benchmarking, and targeted microbenchmarks.   Strong familiarity with modern AI productivity workflows, with the ability to effectively use AI tools.   What We Need   Conduct deep research into cutting-edge CPU application trends, workload characterization, and advanced performance and power modeling techniques.   Build robust profiling, automation, and visualization tools that accelerate workload analysis and streamline production workflows.   Identify microarchitectural bottlenecks, reduce workloads for efficient simulation, and leverage hardware-software co-design principles to propose hardware-aware optimizations.   Enable and optimize critical CPU workloads, utilizing advanced parallel computation techniques to unlock the full potential of Tenstorrent hardware and contribute novel research or patentable ideas.   What You Will Learn   How CPU workload analysis informs next-generation accelerator architecture and performance strategy.   Practical approaches to workload characterization, reduction, performance modeling, and simulation at scale.   How to profile, analyze, and optimize real-world software, ranging from industry-standard SPEC CPU benchmarks to emerging agentic AI workloads across hardware and software boundaries.   Techniques for identifying performance bottlenecks and optimizing the execution of multi-agent AI systems on modern microarchitectures.   How CPU designers, performance architects, and software teams work together to turn analysis into product impact.     USA Hiring Timelines This internship opportunity is available throughout our 3 terms with the following corresponding recruitment cycles: Winter Term: Jan–Apr work