AI computers built on custom silicon and RISC-V CPU designs
Tenstorrent designs AI computing hardware end to end, from RTL in SystemVerilog and UVM verification through MLIR/LLVM compilers to PyTorch and JAX model support. Hiring skews heavily toward senior and staff engineering, with active work on high-performance RISC-V CPUs and chiplet integration. Newer adoption of dbt and Snowflake alongside BI tooling projects points to a back office maturing its data stack as the company scales globally.
Notable leadership hires: Power Characterization Lead
Tenstorrent is a privately held computing company founded in 2016 that builds computers for AI workloads. Its teams span computer architecture, ASIC design, RISC-V CPU development, advanced systems and neural network compilers. The company lists Toronto, ON as headquarters and operates offices across North America, Europe and Asia, including Austin, Silicon Valley, Belgrade, Seoul, Tokyo and Bangalore. It employs between 501 and 1,000 people and hires across countries including Canada, the United States, Japan, Serbia, India and Germany.
Tenstorrent uses SystemVerilog, Verilog, UVM, Cadence and Synopsys tools for chip design, plus C++, Python, MLIR, LLVM, PyTorch, JAX, Kubernetes and Slurm for software and compute infrastructure.
Job posts point to high-performance RISC-V CPU development, custom IP blocks and SoC RTL, chiplet integration into SiP, AI performance on custom silicon and lab infrastructure automation.
Tenstorrent hires in Canada, the United States, Japan, Serbia, India, Germany, Poland, Cyprus, Singapore and Syria, with engineering making up the bulk of open roles.
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Tenstorrent's technology stack, projects, and hiring signals are inferred from public hiring and company data — career pages, public listings, and company web presence — then clustered and de-duplicated. Figures are estimates that refresh over time. Read our full methodology →
This is not an official vendor or customer list. It is a technology-adoption signal inferred from public data, intended for B2B research.