Staff Engineer, Tenstorrent

Physical Design LEC

$100-500k

OTE

Python

Perl

Senior and Expert level

Austin

San Francisco Bay Area

Next-generation computing company building computers for AI

Job no longer available

Next-generation computing company building computers for AI

1001+ employees

B2BArtificial IntelligenceEnterpriseManufacturingDeep TechMachine Learning

Job no longer available

$100-500k

OTE

Python

Perl

Senior and Expert level

Austin

San Francisco Bay Area

1001+ employees

B2BArtificial IntelligenceEnterpriseManufacturingDeep TechMachine Learning

Company mission

To bring unique solutions to the problems facing AI and machine learning.

Job

Company

Role

Who you are

A detail-oriented engineer with strong experience in physical design and logical equivalence checking
Proficient at navigating complex SoC/ASIC design flows on taped out designs, and skilled at problem-solving across synthesis, PnR, and timing closure
Comfortable working across RTL, synthesis, PnR, and sign-off workflows
Skilled at debugging complex implementation or verification mismatches and providing actionable insights
5+ years in physical design with hands-on ownership of LEC and low-power static checks (VCLP/CLP Verify)
Expert with LEC tools and flows, power-aware static verification, and debugging equivalence failures
Experience in synthesis, PnR, timing closure, and logical ECO flows for large-scale SoC or ASIC designs
Advanced scripting skills (Python, Tcl, Perl) to automate checks and processes

What the job involves

We are looking for a Physical Design Engineer, LEC & Implementation to ensure the functional accuracy and consistency of our high-performance AI chips, driving logic equivalence checking (LEC), executing low-power static checks, and working closely with design and implementation teams to debug and optimize complex backend flows
You will own logical equivalence checking and support physical implementation tasks including synthesis, PnR, and timing closure, ensuring design correctness and tapeout readiness
Tenstorrent’s rigorous methodologies for logic equivalence and low-power verification on cutting-edge silicon
How high-performance SoC backend flows are executed and optimized for functional and power goals
Best practices for documenting, automating, and scaling LEC and VCLP flows for next-generation AI accelerators
Cross-functional strategies for efficient debug, handoff, and continuous methodology improvement across world-class silicon teams

Our take

Tenstorrent is a US- and Canada-based semiconductor startup specializing in processors for AI workloads. Rather than building gneral-purpose CPUs or GPus, the company develops custom chips and sofrware optimized for running moder AI models. As demand for AI accelerates, and as a global chip shortage reshapes the semiconductor industry, these trends have become strong tailwinds for Tenstorrent.

The company’s unique approach is to build for this future software, which it believes will be written at a higher level. Combining this with conditional computing, Tenstorrent supports a scalable distributed network approach that is analogous to a human brain.

While the market for specialized AI hardware is destined to be gigantic, the company has to compete with a plethora of hopeful startups (as well as major tech companies like NVIDIA and Qualcomm). That said, Tenstorrent boasts an excellent trajectory so far, with its latest moves including unveiling its high-end Wormhole AI processors, and a partnership with LG which will see the development of chips for "Affectionate Intelligence".

Kirsty

Company Specialist at Welcome to the Jungle

Insights

Top investors

52% employee growth in 12 months

Glassdoor (4.5)

Company

Funding (last 2 of 7 rounds)

Dec 2024

$693m

SERIES D

Jun 2024

$300m

LATE VC

Total funding: $1.3bn

Company HQ

Flemingdon Park, Toronto, ON

Leadership

Jim Keller

(CEO)

Previously Senior VP of Silicon Engineering at Intel Corporation, VP of Autopilot Hardware Engineering at Tesla, Corporate VP and Chief Architect at AMD, and VP of Engineering at Apple.

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