At Apple, we don't just follow industry standards-we define them. We value creative problem-solving and the ability to adapt to new technical challenges. In this role, you will collaborate with diverse hardware teams to ensure our data center infrastructure is not only durable, but built to exceed expectations. From early concepts to field optimization, you will drive innovative reliability strategies and continuous improvement to shape the future of the critical systems powering our global services.
Description
The position is on Apple's innovative Datacenter MLB Reliability Engineering team, wherein we are seeking a highly analytical individual to develop the reliability strategy for our next-generation Data Center motherboards. In this role, you will bridge the gap between component-level and package level physics of failures and system-level availability. You will drive SoC and board integration reliability through rigorous stress testing and physics-of-failure analysis, utilizing advanced statistical modeling to ensure these critical modules meet the uptime and availability requirements of a high-demand data center environment
Minimum Qualifications
BS in Materials Science, Electrical, Mechanical Engineering or an equivalent field desired with 5+ years of experience.
Proficiency in statistical life data analysis
Strong knowledge of Semiconductor package integration, SLI reliability, passive components, PCB reliability, bonding materials, and warpage control.
Ability to apply FMEA (Failure Modes and Effects Analysis) methodologies.
Excellent written and verbal communication skills with the ability to explain complex statistical concepts to non-experts.
Ability to manage multiple projects simultaneously in a fast-paced environment.
Preferred Qualifications
MS or PhD in Reliability Engineering, Systems Engineering, Electrical Engineering, Materials Science, or an equivalent field..
Background in reliability for large-die packages, heterogeneous integration, and high-power server motherboards.
Experience applying reliability modeling (Markov, RBD, Bayesian) and RAS metrics to Data Center architectures.
Proficiency with reliability software (e.g., Weibull++, BlockSim, JMP, Minitab) and scripting languages for statistical modeling like Python, R, or MATLAB.
A record of initiating innovation and continuous improvement in reliability methodologies.
Dynamic and "can-do" attitude with a desire to work with a great team and product.
Exceptional problem-solving abilities and strong attention to detail.
Employers have access to artificial intelligence language tools (“AI”) that help generate and enhance job descriptions and AI may have been used to create this description. The position description has been reviewed for accuracy and Dice believes it to correctly reflect the job opportunity.
- Dice Id: 90733111
- Position Id: 1e8b3c56d03f15ac8cfe9425885d4726
- Posted 10 days ago
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