Top Machine Learning Jobs in Singapore

Develop and deploy AI/ML and analytics solutions for Facilities Mechanical systems (HVAC, chillers, boilers, CDA, cleanroom air). Build predictive maintenance models, dashboards, digital twins, and automation to improve reliability, energy efficiency, and operational decision-making. Collaborate with controls, IT, and operations to integrate SCADA/BMS/PLC data, ensure data quality and governance, and drive digitalization of maintenance workflows while supporting change management in a 24/7 fab environment.

Conduct ML research (deep learning, NLP, statistics) on large and unstructured datasets, implement algorithms in production-quality code, back-test models, and document findings to inform trading strategies.

Develop and deploy product-disposition workflows and deviation alert systems using statistical tools and ML/AI to improve yield, reliability, and quality. Build algorithms for data mining, pattern recognition, and wafer/die screening. Collaborate with Fab, design, and quality teams, mentor team members, and drive technical innovation to meet KPIs like quality, cost, cycle time, and scale.

This internship involves assisting in machine learning development, AI automation, data engineering, and exploring innovative projects to enhance test efficiency and engineering productivity.

Lead development and operation of automated FIB/TEM workflows for NAND technology: run daily TEM/FIB tasks, create automation templates and scripts, apply ML to optimize recipes and data, transfer solutions across teams, collaborate with vendors, ensure data quality and safety, and mentor engineers.

The role focuses on developing product disposition solutions, enhancing yield and reliability through data analysis, and mentoring team members while collaborating across teams.

Lead and grow the Fab10 Electrical & Control Engineering team to ensure safe, reliable semiconductor facility operations. Oversee HVAC electrical distribution, UPS/generators, PLC/SCADA, instrumentation, predictive maintenance, capacity expansion projects, contractor management, budgets, KPIs, and talent development while driving AI/digital adoption and continuous improvement.

Lead large-scale technical risk assessments, design and deploy enterprise cybersecurity controls (including AI-assisted validation) across cloud-native applications, advise stakeholders and engineering teams, and drive adoption of firmwide security frameworks and SDLC-integrated controls.

Responsible for pre-silicon simulation, silicon validation, and TCV development for NAND products, providing technical leadership and driving cross-functional collaboration.

As a Process Control System Engineer, you'll improve manufacturing processes, analyze data, and develop smart control solutions in semiconductor production.

The role involves electrical failure analysis, fault isolation, collaboration with product engineering, and process improvement strategies.

The CE PYE FA Engineer conducts fault isolation and failure analysis, collaborates with engineering teams, and develops innovative techniques to improve defect resolution.

The Staff/Senior Engineer will focus on fault isolation and failure analysis for electrical devices, collaborating with teams to resolve defect issues and improve processes.

Lead the HBM Package Product Engineering team, focusing on yield improvement, cross-functional collaboration, innovation, and mentorship, while managing project execution and technical decision-making.

Design, develop, and deploy software solutions for automated trading systems while collaborating with researchers on technology priorities.

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

As a CE PYE FA Engineer, you'll conduct failure analysis, isolate faults, and collaborate across engineering teams to enhance device reliability.

The Principal Business Intelligence Analyst at Micron drives AI transformation in Smart Manufacturing by leading projects and collaborating across functions to improve manufacturing performance and data utilization using innovative AI solutions.

Lead and grow a team of CMP and BTG engineers to develop and transfer CMP/BTG process modules for 3D NAND. Drive process characterization, DOE-based optimization, process margin and manufacturability improvements, supplier partnerships, pilot ramp/yield support, and adoption of data analytics/AI for predictive modeling and process control.

The role involves developing advanced thin film deposition processes, conducting experiments for process improvement, collaborating with teams, and mentoring junior engineers.

The internship involves hands-on learning in data analytics and machine learning. Interns will build data-driven models, perform statistical analyses, and communicate insights to improve process integration outcomes in semiconductor technology.

The role involves fault isolation and failure analysis support, operating equipment for electrical defect localization, collaborating with teams for defect resolution, and leading a team of technicians.

Design and implement analytics, optimization, and web solutions to improve semiconductor manufacturing efficiency. Develop models for scheduling, capacity, and cycle time, collaborate with stakeholders, manage project requirements and deliverables, and communicate findings to varied audiences.

Lead development, qualification, and manufacturing transfer of advanced packaging (hybrid bonding, TCB, flip chip). Design and analyze DOEs, perform process characterization, root-cause analysis, and yield/reliability improvement. Collaborate cross-functionally, evaluate materials/equipment, apply AI/automation and analytics, and support sample builds and supplier engagements toward high-volume readiness.

Design, develop, deploy, and maintain automation software for factory operations including autonomous material delivery, scheduling, and equipment automation. Collaborate with manufacturing and global automation teams, own end-to-end solution lifecycle, troubleshoot production systems, use data analysis and visualization, and integrate AI-assisted tools to drive continuous improvement and operational efficiency.