Full-Time

Fabric SOC Architect

Confirmed live in the last 24 hours

Tenstorrent

Tenstorrent

501-1,000 employees

Builds advanced computers for AI applications

Hardware
AI & Machine Learning

Compensation Overview

$100k - $500kAnnually

Entry

Remote in USA

US Citizenship Required

Category
Hardware Engineering
System Hardware Engineering
Required Skills
C/C++
Data Analysis
Requirements
  • BS/MS/PhD in EE/ECE/CE/CS
  • Strong grasp of NoC topologies, routing algorithms, queuing, traffic scheduling, and QoS requirements.
  • Expertise in cache coherency protocols (AMBA CHI/AXI protocol), DDR/LPDDR/GDDR memory technology, and IO technology (PCIe/CCIX/CXL).
  • Prior experience or strong understanding of traffic patterns for ML/AI algorithms in a heterogeneous computation system is a plus.
  • Prior experience on formal verification of cache coherence protocols is a plus.
  • Proficient in C/C++ programming. Experience in the development of highly efficient C/C++ CPU models.
Responsibilities
  • Collaborate with the software team and platform architecture team to understand fabric bandwidth and latency requirements and real-time constraints for AI accelerator, CPU, security, and networking traffic. Devise QoS and ordering rules among the CPU, accelerator, and IO coherent/non-coherent traffics.
  • Identify representative traffic patterns for the software applications. Perform data-driven analysis to evaluate fabric topology, QoS, memory architecture , and u-architecture solutions to improve performance, power efficiency, or reduce hardware.
  • Create directory-base cache coherency specification to satisfy performance requirements of coherent multiple-cluster CPU system and accelerator. Tradeoff protocol complexity and performance requirements.
  • Design cache hierarchy to create best performance
  • Set SoC architecture direction based on the data analysis and work with a cross-functional team to achieve the best hardware/software solutions to meet PPA goals.
  • Develop a SoC cycle-accurate performance model includes memory sub-systems, directory-based coherence cache controllers, fabric interconnects, and fabric switches that describe the microarchitecture, use it for evaluation of new features.
  • Collaborate with RTL and Physical design engineers to make power, performance, and area trade-offs.
  • Drive analysis and correlation of performance feature both pre and post-silicon.

Tenstorrent builds advanced computers specifically designed for artificial intelligence applications. Their products include high-performance computing systems that utilize specialized hardware and software solutions, leveraging technologies like ASIC design and RISC-V architecture. Unlike many competitors, Tenstorrent focuses exclusively on AI computing, which allows them to tailor their systems to meet the unique demands of this field. The company's goal is to advance the capabilities of AI through superior computing power, serving clients in various sectors that rely on AI technology.

Company Stage

N/A

Total Funding

$616.8M

Headquarters

Toronto, Canada

Founded

2016

Growth & Insights
Headcount

6 month growth

20%

1 year growth

43%

2 year growth

129%
Simplify Jobs

Simplify's Take

What believers are saying

  • The launch of next-generation Wormhole-based developer kits and workstations could attract a significant developer community, driving innovation and adoption.
  • Collaborations with industry giants like Hyundai and Rapidus indicate strong growth potential and access to advanced manufacturing technologies.
  • The introduction of specialized AI inference acceleration boards like the Grayskull e75 and e150 can capture a niche market in AI and machine learning applications.

What critics are saying

  • The competitive landscape in AI hardware is intense, with major players like NVIDIA and Intel posing significant challenges.
  • Dependence on strategic partnerships for advanced manufacturing and technology development could lead to vulnerabilities if these partnerships falter.

What makes Tenstorrent unique

  • Tenstorrent's use of RISC-V architecture in their AI processors offers a unique alternative to traditional x86 and ARM architectures, providing flexibility and open-source benefits.
  • Their focus on high-performance AI chips and scalable developer kits positions them as a key player in the AI hardware market, particularly for developers seeking robust multi-chip solutions.
  • Strategic partnerships with global entities like Rapidus and C-DAC enhance their capabilities in cutting-edge semiconductor technology and edge AI processing.

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