Datacenter & Agentic AI Workload Performance Analysis Engineer

Tenstorrent is developing high-performance AI technologies and RISC-V computing platforms. The Workload Performance Analysis Engineer will analyze modern datacenter and agentic AI workloads on RISC-V CPUs, characterize performance, and identify opportunities to improve CPU efficiency and scalability. The role collaborates with CPU architects, RTL designers, software engineers, and compiler teams to translate workload insights into architectural improvements.

Responsibilities:

• Help shape the performance of our next-generation RISC-V CPUs across modern datacenter and agentic AI workloads
• Bringing real-world applications onto RISC-V platforms, characterizing their behavior, and using workload analysis to uncover opportunities for better CPU performance, efficiency, and scalability
• Work closely with CPU architects, RTL designers, software engineers, and compiler teams to understand how demanding workloads exercise the CPU and translate those insights into architectural improvements
• Reducing large production workloads for performance modeling
• Correlating simulation results with hardware behavior
• Directly influence CPU architecture and performance across cloud, enterprise, and emerging AI workloads

Requirements:

• You have a strong background in CPU performance analysis, workload characterization, or computer architecture, with experience connecting software behavior to hardware performance
• You understand modern CPU microarchitecture, including superscalar pipelines, speculative execution, memory hierarchies, and vector/SIMD architectures
• You enjoy digging into complex workloads, using profiling and simulation data to identify bottlenecks and turn analysis into actionable recommendations
• You're comfortable working across hardware and software, from CPU microarchitecture and RTL to operating systems, compilers, runtimes, and applications
• You're a strong technical communicator who enjoys collaborating with architects, designers, and software engineers on complex performance problems
• PhD in Computer Engineering, Electrical Engineering, Computer Science, or a related field, with strong research or industry experience in workload characterization, benchmark development, performance analysis, or simulation
• Deep understanding of CPU architecture and RISC-V, including pipelines, speculative execution, vector/SIMD extensions, memory hierarchies, and performance tradeoffs
• Hands-on experience with performance analysis and simulation tools such as Linux perf, strace, QEMU, or CPU microarchitecture simulators
• Strong programming skills in C/C++, Python, Bash/Shell, and assembly or intrinsic programming, with experience working close to the hardware/software boundary
• Strong understanding of systems software, including operating systems, virtualization, compilers, runtimes, and GNU/RISC-V software ecosystems
• This offer of employment is contingent upon the applicant being eligible to access U.S. export-controlled technology
• your citizenship/permanent residency status or ability to obtain prior license approval from the U.S. Commerce Department or applicable federal agency