Top Tech Jobs & Startup Jobs in Singapore

Drive 3D NAND technology integration, roadmap development, architecture enablement, and end-to-end R&D validation. Apply semiconductor device physics, process integration, experiment design, data analytics, AI-assisted modeling, and cross-functional collaboration to solve scaling challenges, improve performance and yield, and develop manufacturable memory technologies.

Drives HBM package product engineering, assembly and cube yield improvement, DPM reduction, cumulative yield ownership, and resolution of packaging quality and RMA issues. Leads process conversions, failure analysis, cross-functional manufacturing initiatives, technical decisions, and AI/ML projects focused on quality, cost, cycle time, and scale. Requires collaboration with global semiconductor, packaging, design, reliability, and manufacturing teams, including international travel.

Develops semiconductor product reliability tests and qualification plans for High Bandwidth Memory products. The role executes reliability testing, investigates device failures through electrical and physical analysis, reduces defect rates, supports process conversions and high-volume manufacturing, manages technical risks, and drives cross-functional resolution with fabrication, design, quality, and technology teams. It also promotes AI-enabled workflow automation, mentors engineers, and supports project prioritization and technical decision-making.

Leads end-to-end SSD system architecture, integration, characterization, validation, debugging, and product execution through high-volume manufacturing. Defines requirements, performance and reliability targets, test strategies, and system trade-offs while coordinating firmware, hardware, NAND, ASIC, validation, and manufacturing teams. Supports customer issues, failure analysis, yield improvement, and AI-assisted analysis workflows.

Leads HBM product reliability engineering, including reliability test-flow development, qualification execution, DPM reduction, failure analysis, process conversions, risk management, and fab improvements. Partners cross-functionally to resolve qualification and RMA issues while optimizing quality, cost, yield, and cycle time. Also develops AI and machine-learning applications for reliability data, promotes AI adoption, and mentors engineering teams.

Lead HBM product reliability engineering, including stress-test flow development, qualification execution, DPM reduction, failure analysis, process conversion, and fab yield improvements. Manage reliability risks, cross-functional projects, technical decisions, and team mentorship. Apply machine learning and AI tools to reliability data, identify failure patterns, and embed AI-driven automation into qualification and engineering workflows.

Leads technical-functional delivery for global HR automation initiatives across hire-to-retire processes. Designs workflows, requirements, data mappings, AI-ready process documentation, controls, UAT materials, and deployment handoffs for platforms such as Workday, ServiceNow, Power Platform, and UiPath. Facilitates HR, IT, AI, data, security, compliance, and vendor stakeholders while managing risks, dependencies, testing, adoption, and benefits realization. Coaches teams on automation design, responsible AI, documentation quality, and operational sustainment.

Develop AI-enabled automation workflows for NAND device characterization and engineering data analysis. Build data pipelines, machine learning models, anomaly detection tools, dashboards, AI assistants, and automated reporting solutions using large-scale semiconductor datasets. The role involves applying data science, generative AI, LLMs, and agentic AI to improve engineering productivity and decision-making while collaborating with cross-functional engineering teams.

Intern will analyze semiconductor backend test processes and equipment performance, evaluate new technologies for high-volume manufacturing, identify yield, quality, reliability, cycle-time, and cost improvements, and apply structured problem-solving, risk assessment, FMEA, data analysis, and responsible AI methods. Deliverables include baseline analyses, performance trend findings, qualification summaries, recommendations, technical reports, presentations, and potentially an AI-enabled proof of concept.

Leads global capital equipment procurement strategy, supplier relationships, commercial negotiations, supply resilience, and cost optimization. Partners with executive and cross-functional stakeholders to align sourcing with semiconductor technology and manufacturing roadmaps. Uses AI, predictive analytics, automation, financial modeling, and market intelligence to improve procurement outcomes. Requires extensive strategic sourcing and supplier management experience, with semiconductor capital equipment expertise preferred.