Top Machine Learning Jobs in Singapore

Owns AI-driven cost-reduction solutions across procurement, facilities, construction, and tool-install processes. Partners with data scientists and engineers to identify use cases, develop business cases, prioritize projects, coordinate global implementation, and measure financial and operational impact. Requires strong analytical, communication, relationship management, and cross-functional leadership skills, with experience in cost initiatives within operations or procurement, preferably in semiconductor construction and tool-install environments.

Owns the identification, prioritization, and implementation of AI solutions that reduce costs across procurement, manufacturing, planning, and program management. Collaborates with data scientists, data engineers, and global business teams to develop business cases, validate ROI, monitor financial and operational impact, and establish new AI use cases. Requires strong cost-project experience, analytical ability, communication skills, and cross-functional leadership, preferably in the semiconductor industry.

Owns AI-driven cost-reduction products and use cases across procurement, operations, engineering, and commercial functions. Collaborates with data scientists, data engineers, and global teams to implement solutions, quantify financial and operational impact, develop ROI-based business cases, prioritize projects, and identify additional opportunities. Requires strong cost-project experience, analytical skills, cross-functional leadership, communication, and relationship management.

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.

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.

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.

Conduct a five-month engineering project optimizing Chemical Mechanical Planarization processes and characterizing equipment in semiconductor manufacturing. Analyze process, metrology, equipment, and manufacturing data using statistical and AI-assisted methods; assess process capability and qualification results; and develop a dashboard, analytics model, or automation tool. Collaborate with cross-functional stakeholders and deliver technical reports, presentations, engineering recommendations, and documented improvement results focused on stability, yield, cost, productivity, or data accessibility.

Develops semiconductor memory reliability test flows, qualification plans, and manufacturing test strategies for HBM products. The role investigates reliability and RMA failures using electrical and physical failure analysis, drives root-cause resolution, supports process conversions, manages technical risks, and collaborates across fab, design, technology, systems, and quality teams. It also applies machine learning and AI automation to reliability data and workflows.

Conduct ML research (deep learning, NLP) on large and unstructured financial datasets, implement algorithms in high-quality code, back-test models, document findings, and collaborate with senior researchers during an 11-week summer internship in Hong Kong or Singapore.

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.

Lead modelling and analysis roadmap for FX products: forecast and monitor FX volatility, optimise trade execution with statistical/ML models, run customer and profitability analyses, and partner with product, trading, risk, and engineering to translate insights into trading and product decisions.

Conduct quantitative research for investment strategies using advanced statistical and mathematical modeling, machine learning, data analysis, portfolio optimization, and algorithm development. Build predictive models and analyze price formation, risk, and financial market drivers. Collaborate with researchers, engineers, and traders to develop scalable systems and solve real-world investment problems.

Provides second-line oversight and credible challenge for AI, privacy, and data risks across APAC. Leads monitoring and testing reviews, control assessments, regulatory engagements, issue remediation, governance reviews, and executive reporting. Translates regulatory expectations into controls, testing methods, evidence requirements, and practical guidance while partnering with business, technology, legal, data, cybersecurity, and model risk stakeholders.

Develop AI Agent prototypes and Python automation solutions to improve productivity in semiconductor photo engineering workflows. Responsibilities include analyzing engineering data, identifying automation opportunities, building data-processing pipelines, creating dashboards, evaluating solution effectiveness, documenting designs, and presenting technical findings. The intern will gain experience with generative AI, large language models, data analytics, and semiconductor manufacturing engineering.

Leads Wise’s APAC product analytics function and a team of approximately 10 analysts. Partners with Product, Banking, and Engineering leaders to shape regional roadmaps, define KPIs, measure impact, generate strategic insights, and improve customer experiences. Responsibilities include developing analytics strategy, coaching analysts, building trusted cross-functional partnerships, and driving data-led organizational change. The role also involves hands-on SQL and Python or R analysis, with potential application of AI and machine learning techniques.

Five-month intern project focused on NAND probe product engineering, test mode integration, Design for Test, silicon validation, and product characterization. The intern will analyze engineering data for yield and failure patterns, develop visualization and automation tools, and explore AI, machine learning, generative AI, and LLM-based solutions for engineering workflows. Deliverables include technical assessments, dashboards, prototypes, reports, and recommendations.

Develop a digital twin and analytics framework for semiconductor photolithography equipment. Analyze utilization, throughput, cycle time, and operational data using statistics, machine learning, simulation, and visualization. Build dashboards and predictive models to identify bottlenecks, evaluate optimization scenarios, and improve equipment productivity. Collaborate with engineering teams, document findings, and present recommendations for manufacturing improvement.

Analyze semiconductor manufacturing data to identify yield detractors, optimize processes, and reduce defects. Build data pipelines from SQL databases, sensor networks, and fabrication logs; apply statistical modeling, machine learning, SPC, DOE, and related analytics. Create automated dashboards and reports using Dash, Plotly, or Angular, and collaborate with manufacturing, equipment, process, and integration engineers to resolve production issues and drive continuous improvement.

Supports a five-month engineering project improving solid-state drive product development workflows. Responsibilities include analyzing engineering processes, developing Python scripts, SQL data pipelines, dashboards, automation solutions, and visualizations, and evaluating their effectiveness. The intern collaborates with engineering and cross-functional stakeholders to define requirements, validate solutions, document findings, and present recommendations. The role provides exposure to semiconductor manufacturing, engineering data analysis, workflow automation, and potentially AI-enabled information retrieval.

Leads global semiconductor manufacturing excellence initiatives, including SEAL deployment, best-known-method standardization, Wafer Per Day improvements, equipment and process optimization, and productivity programs. Identifies and scales AI-enabled engineering solutions, automation, advanced analytics, and digital workflows across manufacturing sites. Partners with global stakeholders, drives pilot adoption, tracks business impact, supports standardization, and mentors teams on AI utilization.

Drives semiconductor diffusion process and equipment performance, productivity, capacity, yield, reliability, and cost improvements. Leads technical investigations, bottleneck reduction, supplier engagement, technology transfers, and cross-functional engineering projects. Uses data analytics, AI, machine learning, statistical methods, automation, and predictive maintenance approaches to improve manufacturing operations. Develops best practices, supports new capabilities, provides technical recommendations, and mentors junior engineers.

Intern will analyze NAND wafer probe and device-level test data, evaluate yield trends and failure signatures, optimize test coverage and efficiency, and develop AI-enabled analytics or automation solutions. Responsibilities include statistical analysis, anomaly detection, data visualization, technical reviews, and collaboration with design, manufacturing, reliability, and test engineering teams. The intern will deliver technical recommendations, an analytical prototype or workflow, and a final report and presentation.

Supports technology and cybersecurity audits across Asia Pacific by assessing risks and controls, conducting walkthroughs and testing, evaluating control effectiveness, drafting reports, validating remediation, and monitoring technology programs. The role requires strong audit judgment, data analytics, stakeholder management, regulatory awareness, and communication skills, with responsibility for producing high-quality workpapers and recommendations while staying current on emerging technologies and regional requirements.

Develop an AI-enabled application, analytical model, or automated workflow addressing a semiconductor process or equipment engineering challenge. Analyze manufacturing and engineering data using statistics, machine learning, Generative AI, large language models, visualization, or automation. Test, validate, document, and present the solution, demonstrating potential improvements in yield, quality, cost, productivity, or cycle time.

Analyze semiconductor manufacturing, inline, parametric, probe, sensor, and fabrication-tool data to identify yield detractors and reduce defects. Build data pipelines, automate analysis, apply statistical modeling and machine learning, support Design of Experiments, and create dashboards and reports using Dash, Plotly, or Angular. Collaborate with manufacturing, process, equipment, and integration engineers to optimize processes and communicate findings.