SlipstreamJobs tracks this role from the company's public career site. Apply directly on the employer's site.
Salary: USD 100,000 - 500,000 / annual
Tenstorrent is seeking a Workload Performance Analysis Engineer to drive the performance of next-generation RISC-V CPUs across modern datacenter and agentic AI workloads. You will sit at the intersection of hardware and software, 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.
You will 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. Your responsibilities include reducing large production workloads for performance modeling, correlating simulation results with hardware behavior, and directly influencing CPU architecture and performance across cloud, enterprise, and emerging AI workloads.
Key responsibilities:
- Analyze and characterize modern datacenter and agentic AI workloads on RISC-V platforms
- Use profiling and simulation data to identify performance bottlenecks
- Collaborate with hardware and software teams to translate workload insights into architectural recommendations
- Reduce complex production workloads into representative workloads and traces for architectural exploration
- Connect workload characterization and performance modeling to CPU design, RTL implementation, emulation, and silicon validation
What you will learn:
- How real-world datacenter and agentic AI workloads influence CPU microarchitecture and architectural decisions
- Hardware/software co-design principles for improving CPU throughput, scalability, and performance-per-watt efficiency
- How to analyze complex production workloads and create representative benchmarks
- How emerging RISC-V capabilities, cloud infrastructure, compiler technology, and AI software stacks are shaping high-performance computing
REQUIREMENTS:
- PhD in Computer Engineering, Electrical Engineering, Computer Science, or 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
- Strong background in CPU performance analysis, workload characterization, or computer architecture, with experience connecting software behavior to hardware performance
- Understanding of modern CPU microarchitecture, including superscalar pipelines, speculative execution, memory hierarchies, and vector/SIMD architectures
- 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
- Ability to work across hardware and software domains, from CPU microarchitecture and RTL to operating systems, compilers, runtimes, and applications
- Strong technical communication and collaboration skills
