Staff Reliability Engineer - AI Hardware & Systems

Tenstorrent

Toronto (OH)

Hybrid

USD 100,000 - 135,000

Full time

14 days+

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Job summary

Tenstorrent is seeking a Staff Reliability Engineer to define the reliability strategy behind its next generation AI computing systems. In this highly visible leadership role, you will drive reliability from architecture through production, partnering across hardware, software, and manufacturing teams to ensure uptime, durability, and quality.

Based in Toronto with a hybrid work model, the role welcomes candidates at varying levels while aligning offers with the selected seniority.

Qualifications

  • 8+ years in reliability engineering, ideally in HPC, AI hardware, or data center systems.
  • Familiar with HALT, HASS, ALT, MTBF, Weibull analysis and FMEA.
  • Ability to explain risks and trade-offs clearly to leadership.
  • Experience leading cross-disciplinary teams across mechanical, electrical, thermal and software.
  • Mentors engineers and leads design reviews that raise the bar.

Responsibilities

  • Set the reliability strategy for next‑gen AI computing systems across data center and workstation products.
  • Lead root‑cause investigations on failures and drive fixes across engineering and the supply chain.
  • Validate advanced cooling systems, vapor chambers, heat pipes, and direct‑to‑chip liquid cooling.
  • Serve as the primary contact for manufacturing partners and suppliers to maintain reliability through NPIs.
  • Mentor engineers and lead design reviews to raise team standards.

Skills

Reliability engineering
HALT
HASS
ALT
MTBF
Weibull analysis
FMEA
Root-cause investigations
Mentoring
Design reviews

Job description

Tenstorrent is seeking a Staff Reliability Engineer to define the reliability strategy behind its next generation AI computing systems. In this highly visible leadership role, you will drive reliability from architecture through production, partnering across hardware, software, and manufacturing teams to ensure uptime, durability, and quality.

Based in Toronto with a hybrid work model, the role welcomes candidates at varying levels while aligning offers with the selected seniority.

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