Tenstorrent

CPU DV Infrastructure and Methodology Engineer - AI Silicon (Austin, Santa Clara or Toronto)

Full-Time in Austin, Santa Clara or Toronto, TX - Mid Level

Tenstorrent is helping enable a new era in artificial intelligence (AI) and deep learning with its breakthrough processor architecture and software. The company’s mission is to deliver orders of magnitude better performance and efficiency for AI workloads from the datacenter to edge of Cloud by co-designing hardware, software and AI algorithms with our unique technology.

Tenstorrent’s architecture scales from datacenter servers to IoT devices with dramatically improved efficiency, flexibility, programmability compared to legacy accelerators including CPUs, GPUs, FPGAs, and TPU-type processors. It is developed by our world-class team with deep expertise in computer architecture, hardware design and verification, systems engineering, compilers, software development, and machine learning algorithms.

Our engineering-based culture is focused on achieving the highest levels of AI innovation across all of Tenstorrent’s technical disciplines. We constantly strive to blend best-in-class aspects of integrity, openness, diversity and collaboration throughout the company: from the CEO to the engineering leadership and to the newest employee who may be a recent college graduate. By joining Tenstorrent, you will be an integral part of a highly accomplished and distinguished team that has many years of experience at companies that include AMD, Arm, Intel and NVIDIA, and that thrives on delivering new, innovative products.

Based in Toronto with operations in Austin and California, Tenstorrent is growing quickly. And, we are proudly backed by top-tier Venture Capital firms including Real Ventures and Eclipse Venture Capital, as well as prominent industry luminaries.

Tenstorrent offers a highly competitive compensation package and benefits, and we are an equal opportunity employer.

AI Silicon Design – CPU DV Infrastructure and Methodology Engineer

At Tenstorrent, we are trailblazing industry’s first dynamic artificial intelligence architecture. We are building best-in-class silicon and software stack for AI/ML workloads.

Role:

Design and development of scalable verification infrastructure for high performance CPUs going into industry leading AI/ML architecture. The person coming into this role will help define DV methodology and create tools and flows that will enable a multi-discipline and multi-site team to execute flawlessly. The person in this role will collaborate with a group of highly experienced engineers across various domains of the AI chip.

Responsibilities:

  • Architecture and hands-on development of scalable solutions that are leveraged for DV testbenches, architectural tools, RTL development and performance modelling across CPU, compute engines and SOCs
  • Development of automation systems for the entire design team
  • Engage with leading industry vendors and 3rd party IP providers, drive integration of external tools and IPs in the design flow
  • Experience with open-source tool-flows and deployment of applicable tools and infrastructure in the design flow; drive tool decisions for build vs leverage vs buy
  • Own regular block/chip/emulation regressions

Experience and qualifications:

  • BS/MS/PhD in EE/ECE/CE/CS with at least 5 years of industry experience
  • Experience with development of DV tools and infrastructure and large-scale regression environments is required, extensive debug of automation workflows
  • Knowledge of EDA tools, strong understanding of simulators. Hands-on experience working with emulation environment and tools is a plus
  • Expertise developing tools for revision control, prior experience with git preferred
  • Very strong programming skills in C/C++, scripting skills in Python, Tcl, Perl
  • Knowledge of multiple testbench methodologies, proficiency in UVM is a plus
  • Strong problem solving and debug skills across various levels of design hierarchies

Locations:

  • Multiple geographies: Austin, Santa Clara, Toronto