Full-Time

Staff Engineer

RTL Design, Fabric and Memory Subsystem

Confirmed live in the last 24 hours

Tenstorrent

Tenstorrent

501-1,000 employees

Builds advanced computers for AI applications

Hardware
AI & Machine Learning

Senior

Boston, MA, USA + 3 more

More locations: Toronto, ON, Canada | Austin, TX, USA | Ottawa, ON, Canada

This role is hybrid, based out of Toronto (ON), Ottawa (ON), Boston (MA), or Austin (TX).

US Citizenship Required

Category
Hardware Engineering
Hardware Validation & Testing
Required Skills
Verilog

You match the following Tenstorrent's candidate preferences

Employers are more likely to interview you if you match these preferences:

Degree
Experience
Requirements
  • BS/MS/PhD in EE/ECE/CE/CS with at least 5+ years of experience in Fabric or Memory subsystem design.
  • Extensive experience with CPU and GPU fabrics, including cache coherence protocols and memory ordering models (e.g., MOESI).
  • Strong understanding of interconnect topologies and protocols such as CHI, AXI, ACE, TileLink. Die-to-die, Ethernet, and I/O protocols are also relevant.
  • Proven ability to tightly couple memory subsystems with CPU cores, optimizing data paths, bandwidth, and latency to meet system requirements.
  • Experience evaluating PPA trade-offs and working with synthesis, timing, and power tools to meet stringent design targets.
  • Hands-on experience with hardware description languages (Verilog, SystemVerilog) and simulators like VCS, NC, and Verilator.
  • Expertise in microarchitecture definition and specification development for complex memory systems.
  • Strong debugging and problem-solving skills across hierarchical levels (core, fabric, and chip) in both pre- and post-silicon environments.
Responsibilities
  • Design and develop the Fabric and Memory subsystems from scratch for a high-performance CPU, working closely with the DV, physical design, and architecture teams.
  • Create RTL implementations in Verilog using both industry-standard tools and open-source infrastructure.
  • Collaborate with cross-functional teams, including design, test, and post-silicon validation, to ensure seamless delivery of the Fabric and Memory subsystems.
  • Evaluate and integrate 3rd-party IP components into the subsystem to meet performance and design goals.
  • Optimize power, performance, and area (PPA) by working closely with performance modeling, DV, and physical design engineers to make informed trade-offs.
  • Conduct experiments with RTL and analyze synthesis, timing, and power results to improve design quality.
  • Debug complex RTL/logic issues across different design hierarchies (core, chip) in both pre-silicon and post-silicon environments.
  • Enhance RTL design infrastructure and tools to streamline development and ensure consistency across projects.

Tenstorrent builds advanced computers specifically designed for artificial intelligence applications. Their products include high-performance computing systems that utilize specialized hardware and software solutions, focusing on technologies like ASIC design and RISC-V architecture. Unlike many competitors, Tenstorrent emphasizes a combination of computer architecture expertise and neural network compilers to optimize performance for AI tasks. The company's goal is to advance the capabilities of AI computing, serving clients in the AI and computing sectors while generating revenue through the sale of their systems and services.

Company Stage

Series D

Total Funding

$1.3B

Headquarters

Toronto, Canada

Founded

2016

Growth & Insights
Headcount

6 month growth

-3%

1 year growth

-5%

2 year growth

-4%
Simplify Jobs

Simplify's Take

What believers are saying

  • RISC-V architecture's growth aligns with Tenstorrent's open-source AI software focus.
  • Automotive AI chip market growth offers lucrative opportunities for Tenstorrent's BOS partnership.
  • Increasing demand for HPC systems could expand Tenstorrent's reach beyond tech industries.

What critics are saying

  • Competition from established AI hardware companies like Nvidia could impact market share.
  • Reliance on open-source software may delay product development timelines.
  • Geopolitical tensions in South Korea and Japan could disrupt Tenstorrent's supply chains.

What makes Tenstorrent unique

  • Tenstorrent leverages RISC-V technology for flexible, open-source AI hardware solutions.
  • The company partners with BOS Semiconductors to develop next-gen automotive AI chips.
  • Tenstorrent's global presence includes offices in key tech hubs like Silicon Valley and Tokyo.

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Benefits

Hybrid Work Options