Tenstorrent

Technology

CPU/AIWorkloadAnalysisIntern

$52–78k ~AI est. Santa Clara, California, United States INTERNSHIP
Market Sentiment
HIGH DEMAND

Neural analysis suggests this role is
optimal for Mid+ candidates.

The Brief

“CPU/AI Workload Analysis Intern at Tenstorrent. Skills: CPU workload analysis, Performance architecture, AI hardware. Conduct research into CPU application trends. Conduct research into workload characterization”

What You'll Achieve.

Maximize hardware performance; Accelerate workload analysis; Streamline production workflows; Unlock full potential of hardware

Industry & Context.

Technology
Problems you'll solve

Solve hard problems; Identify microarchitectural bottlenecks; Troubleshoot performance issues

Eligibility Requirements

Eligible to access U. S. export-controlled technology

What They're Looking For.

Must Have

Ph. D. in Computer Architecture, Ph. D. in Parallel Computing, Ph. D. in Artificial Intelligence/ Machine Learning, publication record, foundation in computer organization, foundation in computer architecture, foundation in parallel computation, foundation in digital logic design, Hands-on with Linux, Hands-on with performance profiling tools, Hands-on with power profiling tools, Hands-on with Silicon PMU profiling, Hands-on with hardware performance counters, Proficient in Shell scripting, Proficient in Python, Proficient in C++, experience in PyTorch, experience in benchmarking, experience in targeted microbenchmarks

Nice to Have

familiarity with modern AI productivity workflows, ability to effectively use AI tools

What You'll Do.

Conduct research into CPU application trends

Conduct research into workload characterization

Conduct research into performance modeling techniques

Conduct research into power modeling techniques

Build profiling tools

Build automation tools

Build visualization tools

Identify microarchitectural bottlenecks

Reduce workloads for simulation

Propose hardware-aware optimizations

Enable critical CPU workloads

Optimize critical CPU workloads

Utilize parallel computation techniques

Contribute novel research ideas

Contribute patentable ideas

How You'll Work.

Team & Collaboration

CPU designers; performance architects; software teams

Full Job Description

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

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