Tenstorrent
Hardware Intern - Architecture, AI HW & SoC (USA)
Austin, Texas, United States +7 · Internship · Posted Oct 7, 2026
- Location
- Austin, Texas, United States
Boston, Massachusetts, United States
Fort Collins, Colorado, United States
Santa Clara, California, United States
Austin, Texas, United States
Boston, Massachusetts, United States
Fort Collins, Colorado, United States
Santa Clara, California, United States - Education
- Currently pursuing a BS, MS, or PhD in EE, ECE, CE, or CS.
- Visa sponsorship
- Employment is contingent on eligibility to access U.S. export-controlled technology. Depending on citizenship or permanent residency status, or ability to obtain prior license approval, employment may not be possible.
About the job
Hardware intern supporting architecture, AI hardware, or SoC teams in designing, modeling, verifying, and integrating chips and AI accelerator hardware.
What you'll do
- Analyze workloads, performance, power, and system requirements; develop architectural models, tradeoff analyses, and specifications.
- Design and verify AI accelerator IP, SoC subsystems, and chip integration.
- Support designs from specification through RTL, verification, qualification, and silicon implementation.
What they ask for
- Currently pursuing a BS, MS, or PhD in EE, ECE, CE, or CS.
- Coursework or projects in digital design, computer architecture, and performance modeling.
- Familiarity with ASIC design concepts, including performance simulations, RTL design or verification, and logic synthesis or timing analysis.
- Scripting and programming skills; experience using AI coding platforms.
Nice to have
- For Architecture: experience with architectural simulators.
- Exposure to RISC-V or other open ISAs; FPGA design experience.
Pay
$50/hr - $70/hr (including base and variable compensation targets)
Tools
Python, PERL, tcl, C/C++, RISC-V, FPGA, RTL
AI focus
Design and develop AI accelerator hardware for high-performance AI workloads; use AI coding platforms and integrate AI tools into technical workflows.
Model-written summary · the original posting is authoritative