Staff Reliability Engineer

Who you are

• You've spent 8+ years in reliability engineering, ideally in high-performance computing, AI hardware, or data center systems
• You're comfortable with the statistical side of the job, HALT, HASS, ALT, MTBF, Weibull analysis, and FMEA are all familiar territory
• You can work through a technical problem in a thermal lab and then explain the risks and trade-offs clearly to leadership
• You're good at bringing people together, mechanical, electrical, thermal, software, and System Dev & Compliance Validation teams, especially when timelines are tight
• You hold a Bachelor's or Master's in Mechanical Engineering, Electrical Engineering, Reliability Engineering, or a related field
• Someone to set the reliability strategy for our next-generation AI computing systems, with MTBF modeling as a core piece
• A strong problem-solver who can lead root-cause investigations and drive fixes across engineering and the supply chain
• Someone who summarizes findings and feeds them back to the Systems Engineering design team, reliability as an ongoing loop, not a one-time check
• A close partner to System Dev & Compliance Validation, helping set hardware up for success ahead of formal testing and certification
• Willingness to travel to third-party test facilities for HALT/HASS, to preplan, oversee testing, resolve DUT issues, and assess design risk in person

What the job involves

• Join Tenstorrent as a Staff Reliability Engineer and help define the reliability strategy behind the next generation of AI computing systems
• In this highly visible technical leadership role, you'll drive reliability from architecture through production, partnering across hardware, software, and manufacturing teams to build high-performance AI platforms that set the standard for uptime, durability, and quality
• If you're passionate about solving complex engineering challenges and influencing products at scale, you'll have the opportunity to shape technology powering the future of AI
• What You Will Learn
• How to build a reliability strategy from scratch for hardware that's pushing the boundaries of AI computing
• How to build predictive models, including MTBF frameworks and accelerated life testing
• How to turn test findings into design improvements through close collaboration with Systems Engineering
• How reliability work sets the stage for validation and certification success
• What it takes to run hands-on testing at manufacturing and test partner sites, including in Taiwan