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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Device Reliability Engineer - **Company:** Avicenatech, Corp. - **Location:** Sunnyvale, CA, United States - **Experience:** Expert - **Contract:** Permanent contract - **Skills:** Artificial Intelligence, Data Centers, Python (Programming Language), MATLAB, Scripting, JMP (Statistical Software), Hardware Testing - **Published:** July 23, 2026 - **Apply:** https://www.indeed.com/viewjob?jk=fe0c163b0eba5ecf ## About the Role * Education: MS or PhD in Electrical Engineering, Materials Science, Physics, or a related field (or BS with equivalent industry experience). * Experience: 5-8+ years in device or product reliability engineering for semiconductor or optoelectronic devices. * Reliability methods: Strong command of accelerated life testing, statistical lifetime modeling, and acceleration-factor/failure-rate analysis. * Standards: Familiarity with reliability qualification standards and methodologies (JEDEC, Telcordia, or equivalent). * Physics of failure: Solid understanding of degradation and wear-out mechanisms in semiconductor/optoelectronic devices. * Analysis skills: Proficiency in statistical analysis and scripting (e.g., Python, MATLAB, JMP) and clear technical reporting., * GaN microLEDs: Prior experience with GaN-based microLED or LED/laser reliability is strongly preferred but not required. * Experience qualifying high-density emitter or detector arrays. * Familiarity with packaging, hybrid-bonding, and heterogeneous-integration reliability. * Experience defining reliability requirements for data-center, optical-module, or high-reliability applications. * Track record building reliability test infrastructure from the ground up in a startup or early-product environment. ## Description As a Device Reliability Engineer at Avicena, you will own the reliability and qualification strategy for our GaN microLED and photodetector devices powering the LightBundle interconnect platform. You will design accelerated stress tests, build lifetime and degradation models, and define the qualification criteria that ensure our devices meet demanding data-center and AI-infrastructure lifetime targets., * Reliability strategy: Define and own device-level reliability roadmaps, specification, qualification test plans (QTP), and acceptance criteria for GaN microLEDs and photodetector arrays. * Accelerated testing: Design and execute accelerated life tests and stress conditions (temperature, current density, humidity, thermal cycling, ESD) and build the associated test hardware/methodology. * Lifetime modeling: Develop degradation and lifetime models (e.g., Arrhenius, acceleration factors, Weibull/lognormal statistics) and project field lifetime from accelerated data. * Failure-mode analysis: Identify and characterize wear-out and degradation mechanisms; partner with Failure Analysis to root-cause reliability fallout and validate fixes. * Qualification: Drive device qualification against internal and industry standards (e.g., JEDEC/Telcordia-style methodologies) and prepare qualification reports for internal and customer use. * Cross-functional influence: Feed reliability learnings back into device design, process, and packaging to improve robustness and margin; contribute to DfR (Design for Reliability) reviews. ## Related Videos - [More efficient software for more efficient microchips](https://www.wearedevelopers.com/videos/1164-more-efficient-software-for-more-efficient-microchips) - [The Sustainability Race: AI's Promises, Pitfalls and Potential](https://www.wearedevelopers.com/videos/100155-the-sustainability-race-ai-s-promises-pitfalls-and-potential) - [JavaScript? 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