Top Engineering Jobs

Develops and optimizes semiconductor wet processes by diagnosing assembly issues, evaluating process equipment and materials, improving yield and cost, and qualifying new process baselines for product introduction. The role supports SPC, FDC, RMS, and APC systems, site-to-site process portability, supplier quality management, audits, and AI-assisted problem solving.

Leads a semiconductor RDA team focused on defect detection, process anomaly identification, inspection technology development, data analysis, and continuous improvement for NAND technology development. Partners with process integration, data science, yield analysis, suppliers, and global manufacturing teams to develop inspection roadmaps, improve detection techniques, manage projects, establish program metrics, and transfer best-known methods across sites. Mentors engineers and drives root-cause analysis, innovation, and technical problem solving.

Leads semiconductor yield analysis for assigned fab modules, identifying yield limiters, investigating root causes, developing yield paretos, and driving sustainable improvements. Performs advanced statistical, inline, probe, and process correlation analyses; collaborates with process integration, engineering, probe, failure analysis, and metrology teams; develops detection methods and custom metrics; automates data extraction and analysis through queries and scripting; supports technology transfers and mentors team members.

Develop, debug, and maintain Python and C/C++ test programs and algorithms for high-bandwidth memory devices. Design and validate test hardware, automate equipment qualification, analyze test data and yields, resolve root causes, support new product introduction, and improve manufacturing test quality, capacity, and cost. Collaborate with global teams on pre- and post-silicon activities, process development, and production test releases.

The role involves establishing and improving process conditions and technologies, enhancing process capabilities, and conducting evaluations and planning for new equipment and materials in semiconductor manufacturing.

Industrial Engineering Intern supporting workflow analysis, process mapping, data analysis, and productivity improvements within planning and warehouse operations. The intern will identify inefficiencies, develop and test prototype digital solutions or MVPs using tools such as Python, Power BI, UiPath, and Microsoft 365, evaluate results, incorporate stakeholder feedback, and present recommendations. AI-enabled tools may be used to support documentation, workflow analysis, automation, and solution development.

Full-time intern developing an AI-enabled predictive analytics framework for SSD test equipment in a semiconductor manufacturing environment. Responsibilities include extracting, cleansing, and analyzing engineering data; building equipment health dashboards; performing statistical analysis; creating anomaly detection methods; identifying predictive maintenance opportunities; documenting results; and presenting recommendations. The role involves Python or SQL, data visualization, AI and machine learning concepts, equipment reliability, and collaboration with cross-functional engineering teams.

Leads CMOS device development, process integration, electrical characterization, technology transfer, and manufacturing ramp for future DRAM technology nodes. Collaborates across device, TCAD, modeling, design, process, product engineering, and manufacturing teams to achieve performance, power, variability, reliability, and productivity targets. Drives exploration of advanced transistor architectures and applies AI, machine learning, analytics, automation, and digital engineering methods to accelerate semiconductor development and improve decision-making.

Leads semiconductor yield deviation and yield-tail investigations in high-volume manufacturing. Monitors probe, wafer, die, bitmap, and parametric data; performs statistical root-cause analysis and failure characterization; and partners cross-functionally to implement corrective actions. Develops analytics, dashboards, automation, and AI-enabled workflows to improve yield, issue sourcing, and engineering productivity. Requires advanced semiconductor knowledge, extensive industry experience, and strong data-analysis capabilities.

Investigate semiconductor yield, quality, and technology issues through electrical and physical failure analysis. Use EMMI, OBIRCH, thermal analysis, SEM, FIB, TEM, and nanoprobing to isolate failures, determine root causes, and improve memory product yield. Collaborate with engineering and R&D teams on process and design improvements, technology introduction, product qualification, yield ramp, and high-volume manufacturing. Develop analytical methods and support continuous improvement initiatives.