Top Tech Jobs & Startup Jobs in Singapore

Manufacturing Equipment Engineering Intern supporting semiconductor manufacturing teams with process improvement, equipment optimization, yield and quality analysis, root cause investigations, and continuous improvement. The role involves analyzing production data, developing data-driven engineering recommendations, collaborating cross-functionally, and using AI, automation, advanced analytics, and digital manufacturing tools. Interns will produce technical documentation, project findings, improvement recommendations, and stakeholder presentations.

Mechanical Engineering Intern supporting a semiconductor facilities project focused on exhaust plume detection, characterization, mitigation, and energy efficiency. Responsibilities include collecting engineering data, analyzing plume behavior using thermodynamics, heat transfer, and fluid mechanics, evaluating detection and reduction methods, preparing engineering documentation, and presenting recommendations. The intern will use Excel, potentially AutoCAD, and AI-enabled tools while gaining experience with industrial exhaust and facilities mechanical systems.

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.

Own the AI product vision, strategy, roadmap, and lifecycle across procurement and planning. Lead discovery, requirements, backlog prioritization, data-readiness assessments, and cross-functional delivery from proof of concept through production adoption. Partner with data scientists, data engineers, executives, procurement teams, and external stakeholders to develop AI, generative AI, and agentic solutions that improve cost efficiency, productivity, decision-making, and business-process automation.

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.

Leads HBM product engineering and media health manufacturing activities, including test-flow development, validation, yield improvement, reliability, circuit debugging, test coverage optimization, cost reduction, and DFT strategy. Manages technical projects, makes risk and prioritization decisions, mentors engineers, and collaborates with manufacturing, design, technology development, quality, and reliability teams to deliver next-generation HBM products.

Design, build, and deploy production AI applications for semiconductor manufacturing. Responsibilities include developing full-stack machine learning solutions, APIs, web applications, data pipelines, LLM and agentic AI capabilities, analytics, and integrations with robotics, automation, control systems, and MES platforms. The role also leads deployment, observability, CI/CD, model evaluation, responsible AI, optimization, testing, mentoring, and technical documentation across global manufacturing environments.

Leads the architecture and delivery of production AI products for autonomous semiconductor manufacturing. Responsibilities span data engineering, machine learning, GenAI, full-stack applications, robotics integration, digital twins, simulation, and edge-to-cloud deployment. The role also owns CI/CD, observability, model evaluation, Responsible AI, performance optimization, technical mentorship, and cross-functional delivery across software, manufacturing, robotics, and infrastructure teams.

Lead and coordinate semiconductor package qualification and reliability testing for new products; develop test plans and screening methods; drive root-cause analysis and 8D corrective actions; present technical reports; and liaise with internal teams and customers on package quality and release recommendations.