Hardware Reliability Engineering

Own the reliability of the advanced packages and systems that turn our AI accelerator silicon into products that survive years in the field. You'll define how we qualify 2.5D/3D and heterogeneously-integrated packages, model their physics of failure, drive root-cause when things fail, and build the reliability engineering that lets us predict lifetime under real workloads. You'll sit at the seam between silicon/packaging and the systems our accelerators run in, partner closely with our OSATs, and own the answer to "will this hold up in the field - and for how long?

Reliability analysis & risk assessment: Conduct physics-of-failure modeling for advanced accelerator packaging; assess thermal, mechanical, and electrical stressors; Failure analysis & root cause: Lead failure-mode analysis using C-SAM, X-ray CT, SEM, TEM, FIB, and EBSD; Reliability physics & lifetime prediction: Build and apply models (Coffin-Manson, Arrhenius, Black's equation) and FEA-based stress simulation to predict field lifetime and FIT under real accelerator thermal and power profiles

define requirements, ensure JEDEC/IPC/IEEE/MIL-STD compliance, monitor OSAT performance, and support supplier audits and qualifications

Assess thermal, mechanical, and electrical stress interactions across package, board, and the system the accelerator ships in; drive design-for-reliability into the package and board ↔ package interface with packaging, materials, SI/PI, and thermal

Develop design guidelines and reliability best practices, and own the reliability data presented to internal teams and customers

Fleet & data-center reliability: Translate package- and system-level reliability into fleet availability targets - AFR, FIT, MTBF/MTTR, and availability "nines"; drive detection and mitigation of silent data corruption (SDC) / silent data errors in production; close the loop from field telemetry, returns, and RMA back into design and qual (reliability growth); partner with data-center operations, SRE/hardware-ops, and customers on serviceability and uptime for large-scale training and inference

D. in Materials Science, Mechanical Engineering, Electrical Engineering, Applied Physics, or related field

• 5+ years in 2.5D/3D advanced packaging reliability
• Deep command of physics-of-failure methodology and strong materials-science knowledge, particularly interconnects and interfaces
• Proficiency in statistical reliability analysis (Weibull, lognormal, acceleration modeling; JMP, Minitab, or Python)
• Hands-on failure analysis with C-SAM, X-ray CT, SEM, TEM, FIB, and EBSD
• Heterogeneous integration, fan-out packaging, chiplet architectures, HBM, or silicon-photonics packaging
• Electrical reliability mechanisms (electromigration, dielectric/TDDB breakdown)
• Design-for-reliability (DFR), prognostics, and health management for electronic systems
• customer-facing qualification experience

Additional compensation: equity grant per company guidelines; medical / dental / vision; Visa Sponsorship

DensityAI sponsors qualified candidates for H-1B, O-1, TN, E-3, and other employment-based visas, and we welcome applicants on F-1 OPT and STEM-OPT. we provide immigration support to secure or transfer status.

We do not discriminate on the basis of race, color, religious creed, national origin, ancestry, physical or mental disability, medical condition, genetic information, marital status, sex, gender, gender identity, gender expression, age (40+), sexual orientation, military or veteran status, pregnancy, or any other status protected by law. Additional compensation: equity grant per company guidelines; medical / dental / vision; Visa Sponsorship

DensityAI sponsors qualified candidates for H-1B, O-1, TN, E-3, and other employment-based visas, and we welcome applicants on F-1 OPT and STEM-OPT. we provide immigration support to secure or transfer status.

We do not discriminate on the basis of race, color, religious creed, national origin, ancestry, physical or mental disability, medical condition, genetic information, marital status, sex, gender, gender identity, gender expression, age (40+), sexual orientation, military or veteran status, pregnancy, or any other status protected by law.