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Silicon Power & Characterization Lead
Austin, Texas, United States; Santa Clara, California, United States; Toronto, Ontario, Canada
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On-site
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Full-time
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2w ago
Tenstorrent is leading the industry on cutting-edge AI technology, revolutionizing performance expectations, ease of use, and cost efficiency. With AI redefining the computing paradigm, solutions must evolve to unify innovations in software models, compilers, platforms, networking, and semiconductors. Our diverse team of technologists have developed a high performance RISC-V CPU from scratch, and share a passion for AI and a deep desire to build the best AI platform possible. We value collaboration, curiosity, and a commitment to solving hard problems. We are growing our team and looking for contributors of all seniorities.
Tenstorrent is seeking a highly skilled and experienced Engineer to lead post-silicon power characterization and correlation activities for cutting-edge semiconductor products. In this role, you will be responsible for developing and executing detailed power measurement strategies on silicon, correlating results with pre-silicon models, and driving improvements across power architecture, design, and modeling methodologies. You will serve as a key technical leader, interfacing across design, architecture, validation, and systems teams to ensure silicon meets power and performance specifications under all operating conditions.
This role is hybrid, based out of Toronto, ON or Austin, TX or Santa Clara, CA.
We welcome candidates at various experience levels for this role. During the interview process, candidates will be assessed for the appropriate level, and offers will align with that level, which may differ from the one in this posting.
Who you are
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A Principal-level engineer with 8+ years in silicon power analysis and characterization, and a Master’s or PhD in EE, CE, or related field.
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Deep understanding of digital and mixed-signal power domains, including DVFS, leakage vs. dynamic power, and power gating.
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Highly proficient in lab-based power measurement using oscilloscopes, current probes, power analyzers, and SMUs, plus Python/Perl/MATLAB for automation and analytics.
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A strong debugger and collaborator, comfortable driving cross-functional investigations and clearly communicating technical findings.
What we need
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Own the post-silicon power measurement strategy end-to-end across operating modes, voltages, frequencies, and workloads.
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Build and maintain lab infrastructure, automated workflows, and data analysis pipelines for high-fidelity, repeatable power characterization.
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Correlate silicon power data to pre-silicon models (RTL, gate-level, sign-off), drive root-cause analysis, and refine power estimation methodologies with design and modeling teams.
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Characterize power across PVT corners and work with bring-up/validation teams to develop test content, debug power anomalies, and ensure products meet power and performance specs.
What you will learn
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How state-of-the-art So Cs behave in real silicon across diverse workloads, system configurations, and operating conditions.
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How to influence power architecture, RTL design, and modeling flows by feeding silicon insights directly back into early design phases.
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Best practices for building scalable, automated post-silicon power infrastructures that support multiple products and generations.
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Advanced correlation, margining, and variability analysis techniques that deepen your expertise in both SoC-level power and system-level behavior.
Compensation for all engineers at Tenstorrent ranges from $100k - $500k including base and variable compensation targets. Experience, skills, education, background and location all impact the actual offer made.
Tenstorrent offers a highly competitive compensation package and benefits, and we are an equal opportunity employer.
This offer of employment is contingent upon the applicant being eligible to access U.S. export-controlled technology. Due to U.S. export laws, including those codified in the U.S. Export Administration Regulations (EAR), the Company is required to ensure compliance with these laws when transferring technology to nationals of certain countries (such as EAR Country Groups D:1, E1, and E2). These requirements apply to persons located in the U.S. and all countries outside the U.S. As the position offered will have direct and/or indirect access to information, systems, or technologies subject to these laws, the offer may be contingent upon your citizenship/permanent residency status or ability to obtain prior license approval from the U.S. Commerce Department or applicable federal agency. If employment is not possible due to U.S. export laws, any offer of employment will be rescinded.
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Tenstorrentについて

Tenstorrent
Series CTenstorrent is a semiconductor company that develops AI accelerator chips and software for machine learning workloads. The company focuses on creating scalable processor architectures for data centers and edge computing applications.
201-500
従業員数
Toronto
本社所在地
$2.6B
企業価値
レビュー
3.8
10件のレビュー
ワークライフバランス
3.2
報酬
2.8
企業文化
4.1
キャリア
3.4
経営陣
4.0
72%
友人に勧める
良い点
Supportive management and strong leadership
Great team culture and fantastic colleagues
Cutting-edge technology and challenging projects
改善点
Heavy workload and frequent overtime
Fast-paced and stressful environment
Below industry standard salary
給与レンジ
24件のデータ
Staff/L6
Staff/L6 · Staff Field Application Engineer
1件のレポート
$261,520
年収総額
基本給
$201,323
ストック
-
ボーナス
-
$261,520
$261,520
ニュース&話題
Former Tenstorrent Execs Launch AI& to Build Japan’s Full-stack AI Infrastructure - EE Times Asia
EE Times Asia
News
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1w ago
Ex-Tenstorrent Execs Start Cloud Provider, AI Lab in Japan - EE Times
EE Times
News
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3w ago
Interview with Toloka CEO (in Russian)
If you happen to understand Russian, here is a 2h interview with Toloka CEO Olga Megorskaya. Few things that I noted: * Industry is called Human Data, the biggest competitor is Scale AI. Basically they know how to produce human-generated data of a high quality that is used to train/post-train AI. These days it's a highly skilled people, sometimes with PhDs or many years of experience, but humans are unreliable, don't follow instructions, etc. - so it is a challenge to produce high quality data
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3w ago
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28
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7
These AI Workstations Look Like PCs but Pack a Stronger Punch - IEEE Spectrum
IEEE Spectrum
News
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3w ago



