Top Tech Jobs & Startup Jobs in Singapore

The Engineer will develop and test security firmware for SSD products, ensure quality assurance, communicate project statuses, and utilize AI tools to enhance efficiency while collaborating with team members.

The Staff Engineer will perform high-quality TEM analysis, develop advanced characterization methods, and collaborate with cross-functional teams to support memory technology projects.

The role involves leading global teams in HBM product yield and quality improvements, managing projects, and driving technical innovations in semiconductor processes.

Lead R&D and operations in advanced metrology processes, develop methods for accuracy and precision, and mentor engineers in a semiconductor manufacturing context.

Lead PAC business processes and projects at Micron, aiming for best-in-class performance, while supporting global teams and driving continuous improvements.

As a Data Science Engineer, you will analyze large datasets, develop predictive models, and work collaboratively to enhance data tools and processes.

The intern will work on enhancing manufacturing processes in dry etch operations using AI techniques, gaining knowledge in preventive maintenance and repair procedures.

Process Integration Engineer responsible for improving yield, quality, and output on NAND Flash production. Design and analyze process experiments, collect and interpret data, lead cross-functional teams to resolve process issues, collaborate with global partners and production engineering, and integrate AI-assisted tools to enhance efficiency and continuous improvement.

Design and execute functional and design validation flows for NAND devices using simulation. Build deterministic and random test programs (RSG), automation frameworks (C/C++, Python, Perl), and data-driven dashboards. Apply AI/ML for analytics, anomaly detection, and triage to improve coverage and debug. Perform deep failure analysis, drive root-cause resolution with cross-functional teams, and prepare infrastructure for product release.

Analyze semiconductor manufacturing data to identify yield detractors, build data pipelines, apply statistical and machine learning models for yield improvement, support DOE experiments, and create automated dashboards and reports for engineering stakeholders.