Top Machine Learning Jobs in Singapore

Lead HBM product reliability test development and execution to reduce DPM, drive intrinsic/extrinsic reliability, debug qual/RMA failures via EFA/PFA, enable process conversions with fab, apply ML/AI to reliability datasets, mentor team, and collaborate cross-functionally to meet quality, cost, and cycle-time KPIs.

Leads High Bandwidth Memory product development from introduction through high-volume production. Owns technical program requirements, milestones, reviews, risk mitigation, decision-making, and cross-functional coordination across engineering, quality, supply chain, packaging, test, and manufacturing teams. Represents programs to executives, drives change management, and develops distributed team members through mentorship, coaching, evaluations, and accountability.

Deploys, configures, optimizes, and supports CrowdStrike Falcon’s AI-powered detection and response capabilities. The role develops automation playbooks and API integrations, tunes machine-learning detection models, troubleshoots customer issues, supports threat hunting and forensic analysis, integrates security workflows, and leads AI workshops. It also requires customer engagement, technical presentations, project prioritization, cross-functional leadership, and mentoring while applying cybersecurity, AI/ML, and platform deployment expertise.

Develops and optimizes semiconductor process control systems to improve yield, quality, reliability, cost, and productivity. Responsibilities include data analysis, process modeling, statistical and fault detection methods, equipment and material evaluation, control limit and OCAP development, supplier coordination, system integration, and smart manufacturing solutions using machine learning, IIoT, and advanced controls. The role also provides technical support, training, and cross-functional collaboration across process and equipment teams.

Develops semiconductor product reliability test flows, qualification plans, and manufacturing test strategies for HBM products. Leads DPM reduction, failure analysis, root-cause resolution, process conversions, risk management, and high-volume manufacturing support. Collaborates with fab, design, technology development, systems, and quality teams. Applies Python, JMP, machine learning, and AI tools to reliability datasets and workflows while making technical decisions and mentoring others.

Analyzes logistics performance, transportation costs, inventory flows, service levels, and operational KPIs. Leads global logistics transformation projects, develops dashboards and reports, identifies cost-saving opportunities, and implements AI, automation, and digital workflow solutions. Manages logistics systems including SAP and transportation platforms, gathers requirements, coordinates testing and deployments, maintains documentation, supports training, and drives process standardization, governance, continuous improvement, and logistics network optimization.

Develop and optimize semiconductor assembly and packaging processes, characterize process windows, improve yield and reliability, and lead root-cause and failure-analysis investigations. Support NPI, product qualification, technology transfers, process readiness, and high-volume manufacturing. Use statistical methods, manufacturing datasets, visualization, machine learning, and AI-enabled monitoring to identify trends and optimize processes. Provide technical leadership, mentor engineers, and coordinate cross-functional teams across process development, manufacturing, yield, reliability, integration, and equipment engineering.

Develops semiconductor product reliability stress tests, qualification plans, and manufacturing test flows for High Bandwidth Memory products. Investigates qualification and field failures using electrical and physical failure analysis, drives root-cause resolution, supports process conversions and high-volume manufacturing, and manages reliability risks and cross-functional projects. Applies Python, JMP, machine learning, and AI tools to analyze reliability data, identify anomalies, improve workflows, and reduce defect-per-million rates.

Leads global strategy, governance, deployment, and continuous improvement of semiconductor front-end quality and equipment-control systems. Oversees FDC, alarms, equipment monitoring, risk assessment, lifecycle controls, analytics, automation, machine learning, and generative AI initiatives. Defines processes, requirements, standards, metrics, and best practices while partnering with fabs, IT, engineering, and analytics teams. Leads technical programs, prototypes, deployment, validation, cross-site alignment, and operational improvements supporting product quality, yield, reliability, and manufacturing continuity.

Leads analytics for Wise’s financial crime and risk controls teams, turning complex data into actionable insights, metrics, reports, visualizations, and product recommendations. Partners with product managers, designers, data scientists, engineers, and operations teams to detect and mitigate financial crime while balancing risk with customer experience. Builds scalable risk frameworks, identifies emerging threats, and manages a team of three analysts.

Design and deploy software and data-analytics solutions for Probe operations: real-time reporting, monitoring, automation of material tracking and validation, and AI-assisted efficiency improvements. Collaborate globally to identify process improvements and implement software and process changes to reduce resolution turnaround and ensure product quality.

Develop analytics, operations-research and machine-learning solutions and web applications to improve semiconductor manufacturing efficiency and scheduling. Manage requirements, stakeholders, and delivery; collaborate across teams; integrate AI-assisted tools; and support continuous improvement in capacity, cycle-time, and scheduling optimization.

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.

Own the strategic roadmap for AI-enabled yield smart manufacturing solutions. Identify solution gaps, define business opportunities, and lead global projects with fab engineers, AI engineers, and data scientists. Apply AI, GenAI, predictive analytics, and machine learning to yield improvement, process optimization, technology development, and intelligent decision support. Use performance metrics and domain expertise to address manufacturing challenges and deliver integrated solutions.

Own smart manufacturing and AI-enabled yield analysis solutions from discovery through implementation. Diagnose process gaps, define requirements with Industry 4.0 users, standardize scalable tools, build ROI-based business cases, prioritize initiatives, and coordinate global teams including architects, data scientists, data engineers, and machine learning engineers. Use operational metrics to identify improvements and provide functional guidance on system capabilities and interfaces.

Design and implement advanced process control, automation, and analytics solutions for semiconductor manufacturing. Collaborate with process teams, apply statistical analysis and machine learning to improve yields, maintain global control applications, and deliver training while promoting continuous improvement and responsible use of AI tools.

Lead a full-stack engineering team building scalable websites, CMS platforms, customer-facing applications, and growth infrastructure. Set technical direction across frontend, backend, APIs, content platforms, and integrations while enabling experimentation, personalization, SEO, performance, and conversion optimization. Mentor engineers, drive engineering excellence, and partner with Product, Design, Marketing, and Data Science to deliver measurable customer acquisition and growth outcomes.

Performs electrical device characterization, fault isolation, and physical failure analysis for NAND product qualifications, new device introductions, and manufacturing issues. The role identifies electrical and process failure mechanisms, collaborates with process, product, test, and quality teams, develops failure-analysis techniques, presents findings, and maintains analysis equipment. It also incorporates AI, machine learning, data analytics, and automation to improve semiconductor engineering and yield enhancement.

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 infrastructure platform architecture across cloud-based technologies, translating complex technical issues for leadership, evaluating emerging technologies, improving governance, and guiding engineering teams. Develops reusable AI-enabled engineering patterns with validation, security, resiliency, and auditability controls. Partners with stakeholders, vendors, and technical teams to align local solutions with strategic architecture targets and influence product design, functionality, and technical operations.

The role involves developing AI and ML solutions for semiconductor workflows, training Citizen Data Scientists, and integrating intelligent agents into engineering processes.

Conduct innovative machine learning research and develop scalable, robust models for financial markets across asset classes. Apply deep learning, sequence and time-series modeling, natural language processing, large language models, pre-training, fine-tuning, and reinforcement learning to model price formation, market behavior, and risk. Design, implement, optimize, and deploy models using Python and modern machine learning frameworks while collaborating with quantitative researchers, engineers, and traders.

Leads semiconductor manufacturing and equipment capability roadmaps, supplier technology partnerships, global manufacturing strategy, and cross-site productivity initiatives. Improves CVD equipment performance, reliability, throughput, utilization, cycle time, and cost efficiency through continuous improvement, root-cause analysis, technology transfer, and process qualification. Applies AI, machine learning, advanced analytics, and digital manufacturing solutions to optimize equipment and manufacturing operations while mentoring engineers.

Supports CFD simulation delivery for marine propulsion and other industrial engineering projects. Builds models from geometry cleanup and meshing through simulation and post-processing, using OpenFOAM or comparable tools. Contributes to automation, parametric CAD workflows, simulation datasets, and machine learning surrogate development. Works with data scientists and customers under senior guidance, uses cloud and HPC resources, presents results, and travels occasionally for customer engagements.