Top Machine Learning Jobs in Singapore

Lead Fab10 electrical and control engineering for safe, reliable semiconductor facility operations. Manage team performance, HVAC/PDU/HV-MV-LV power systems, PLC/SCADA, predictive maintenance, asset management, and obsolescence strategies. Support capacity expansions, tool installs, contractor oversight, energy efficiency, and adoption of AI/ML and digital technologies to improve reliability and operational excellence.

Lead FP&A partnership with global commercial teams, own budgeting/forecasting, build GTM KPI/reporting, analyze profitability and unit economics, drive AI-enabled FP&A automation, and mentor junior staff to improve processes and decision-making.

Conduct quantitative research and statistical analysis on crypto markets to develop, backtest, and implement automated trading strategies. Work with large and unconventional data sets to build valuation models, refine algorithms, and deploy signals in live trading to drive P&L growth.

Summer intern role building high-performance, large-data research platforms and web frameworks. Collaborate in small teams to create tools for trading strategies, applying distributed computing, NLP, and machine learning.

Engineers at Citadel work in small teams to develop high-performing technology under quick cycles. They focus on creating tools for trading strategies and data research platforms.

The Senior Product Owner will lead smart manufacturing solutions and apply AI and machine learning in Micron's processes, requiring semiconductor experience.

The CE PYE FA Engineer will provide fault isolation and failure analysis support, collaborate on defect resolution, and innovate analysis techniques.

As a CE PYE FA Engineer, you will perform fault isolation and failure analysis, collaborate with teams, and develop new techniques to enhance operational efficiency.

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.

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.

Lead advanced data analytics and ML initiatives to improve yield, quality, and reliability for HBM products. Develop ML/DL models, build data infrastructure, integrate solutions into disposition workflows, mentor team members, and collaborate cross-functionally to optimize KPIs including quality, cost, cycle time, and scale.

Lead product strategy for real-time and post-transaction monitoring across payments. Own rules, alerting, workflows, investigator tooling, client-specific controls, and AI-driven detection, partnering with Risk, Compliance, Data, and Engineering to reduce fraud while preserving customer experience and operational efficiency.

Lead product strategy and execution for real-time and post-transaction monitoring across payments. Own rule design, alert optimisation, investigator tooling, client-specific controls, and scalable detection infrastructure. Partner with Risk, Compliance, Operations, Data, and Engineering to reduce fraud, leverage AI/analytics, automate workflows, and ensure AML/regulatory alignment while preserving customer experience.

Lead product strategy for real-time and post-transaction payment monitoring. Own rule design, alert optimisation, investigator tooling, client-specific controls, and AI-driven detection improvements while partnering with Risk, Compliance, Data, Operations, and Engineering to reduce fraud and operational overhead and ensure regulatory alignment.

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.

As a Customer Success Engineer, you will manage enterprise customer relationships, provide technical expertise, and drive integration and adoption of Deepgram's voice AI solutions, ensuring customer success and identifying growth opportunities.

The role focuses on designing, developing, and maintaining automation solutions for factory operations, improving productivity and system efficiency through collaboration with teams and data analysis.

Lead a distributed Process Integration team for HBM NPI, set PI strategy and governance, coordinate cross-site NPI execution, manage risks and yield ramp, drive AI-enabled analytics adoption, and build leadership and capability across sites.

Define and develop reliability stress tests and qualification plans for HBM products; drive DPM reduction and root-cause analysis using EFA/PFA; support process conversions and HVM, manage qualification execution and risk, collaborate cross-functionally, and apply AI/ML to reliability datasets to improve test flows and productivity.

The Senior Engineer will enhance production efficiency, manage semiconductor equipment processes, and lead improvements in memory product development through engineering methods and collaboration.

Lead product ownership for smart manufacturing AI solutions in semiconductor manufacturing. Define requirements, partner with data scientists and engineers, prototype AI/big-data solutions, drive ROI, manage Jira/Confluence, ensure enterprise-grade standards, and measure production outcomes to improve yield, quality, and test performance.

Design, implement, and maintain data-driven processes and analytics solutions. Collect, cleanse, automate, and prepare data from disparate sources. Build KPIs and dashboards, apply statistical and machine learning methods, collaborate with stakeholders, perform testing and deployment, and train users to enable data-driven decision making and process improvements.

Lead development of advanced dry etch processes for NAND technology, inventing plasma chemistries and equipment capabilities. Use AI/ML, analytics, and automation to accelerate process pathfinding, collaborate with integration and device teams, and drive manufacturability and yield improvements across semiconductor process domains.

Operate and maintain SEMs and related sample-prep tools for NAND development, perform construction analysis, troubleshoot and optimize tools, support engineers, and help develop automated/AI-assisted lab workflows and reporting.

Lead Package and HBM Product Engineering, improve yields, resolve packaging issues, mentor team members, and collaborate across functions for product improvement.