Top Engineering Jobs in Singapore

Develop and evaluate a Python-based automated framework for Non-Zero-Offset control in high-volume semiconductor photo processes. The intern will analyze inline, recipe, metrology, and historical process data; apply statistical and machine-learning methods; create visualizations and automation prototypes; and validate findings with engineering subject matter experts. Deliverables include cleaned datasets, reusable scripts, predictive or risk-identification models, technical documentation, and a final presentation.

Leads Micron’s HBM Product System Engineering Media Health team in developing, validating, and manufacturing next-generation HBM products. Responsibilities include optimizing test coverage, improving device and stacked-die yields, reducing test time and costs, resolving manufacturing, qualification, and RMA issues, and supporting circuit analysis, CAD, and Verilog validation. The role manages complex technical projects, makes risk and prioritization decisions, collaborates cross-functionally, mentors engineers, and drives AI-enabled automation and innovation. The position is onsite in Singapore with international travel.

Develops and optimizes semiconductor fabrication processes and equipment to improve yield, quality, reliability, cost, cycle time, and productivity. Responsibilities include setting process parameters, troubleshooting manufacturing issues, conducting root-cause and failure analyses, qualifying new processes and equipment, managing process improvements, analyzing statistical data, supporting audits, and collaborating with material suppliers. The engineer also uses AI-enabled tools responsibly to improve operational effectiveness.

Leads global semiconductor packaging product yield, quality improvement, process integration, and new product introduction initiatives. Drives PI Loop taskforces, process-flow optimization, business-process standardization, benchmarking, and cross-functional project execution across fabs and engineering teams. Applies semiconductor expertise, AI-enabled engineering tools, advanced analytics, and digital transformation to accelerate problem solving, improve decision-making, and increase productivity. Requires regular collaboration, presentations, and travel to Micron fab locations.

Analyze and characterize semiconductor manufacturing defects, troubleshoot wafer fabrication problems, perform root cause analysis, and improve process capability, yield, quality, and cost. The role evaluates equipment and materials, manages process improvement projects, investigates process deviations, and recommends corrective actions and manufacturing changes. It collaborates across engineering and manufacturing teams while applying AI-assisted tools to improve analysis and operational effectiveness.

Supports the design, operation, optimization, and troubleshooting of chemical and gas delivery systems for semiconductor manufacturing facilities. Responsibilities include capacity planning, code compliance, equipment integration, infrastructure planning, contractor and supplier coordination, SOP improvement, safety verification, construction inspection, cost estimation, and continuous improvement. The engineer also supports new equipment startups, facility layouts, quality management processes, and responsible use of AI-enabled tools.

Support probe area capacity and cycle-time planning, identify and resolve constraints, deploy manufacturing systems, drive productivity and quality improvements, set up automated disposition systems, support new NAND device setups, integrate AI-enabled analytics, and maintain QMS and cross-functional coordination to meet business objectives.

Perform electrical and physical failure analysis of semiconductor devices using advanced FA tools (FIB, SEM, EDX, X-ray, micro-prober). Analyze test data with Bash/Python in Unix, identify failure mechanisms, drive corrective actions with product and process teams, develop FA techniques and automation, maintain lab safety and +6S standards, prepare FA reports, mentor technicians, and use AI-enabled tools to accelerate investigations and improve workflows.

Manage end-to-end reliability stress tests and package qualification (thermal cycling, HAST, CSAM, HTOL, etc.). Maintain process of record, lead equipment qualification, define control plans, analyze performance data, drive continuous improvements, and integrate AI-enabled reporting and automation with lab systems.

Leads NAND product engineering and cross-functional development from silicon through SSD integration and customer qualification. Translates business requirements into qualification specifications, develops AI-enabled workflows for data analysis and program management, coordinates engineering, fabrication, testing, quality, supply chain, and design teams, and guides resolution of NAND-system issues. Organizes capability reviews, leads product development meetings, and supports on-time delivery of next-generation NAND products.