Data Center - MLB Reliability Engineer

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. 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 environmentLead the board-level reliability strategy for high-performance computing (HPC) motherboards and server systems. Utilize Design and Process FMEA to identify, categorize, and eliminate failure modes early in the design cycle. Apply physics-of-failure principles to analyze semiconductor packages, Second Level Interconnects (SLI), and PCB materials. Develop advanced reliability models such as Reliability Block Diagrams (RBDs), Markov Chains, and Bayesian analysis to quantify board-level risk and its contribution to overall system availability. Translate Reliability, Availability, and Serviceability (RAS) metrics for large-scale data center deployments into actionable board-level design targets and validation criteria. Design and execute comprehensive test plans including Mechanical Stress, Environmental Testing, and Accelerated Life Testing (ALT). Drive rigorous Root Cause Analysis (RCA) and perform statistical analysis to assess design maturity. Work with cross-functional teams to translate system-level availability requirements into component specifications.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.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.