Top Machine Learning Jobs in Singapore

Intern will develop and deploy a digital Target Traveler solution for semiconductor Probe operations. Responsibilities include analyzing process flows, defining control requirements, configuring workflows, creating data collection and compliance dashboards, monitoring deviations, and recommending process improvements. The role involves collaboration with engineering, manufacturing, quality, and IT teams while building experience in semiconductor process control, analytics, workflow automation, digital transformation, and AI-enabled manufacturing.

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.

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.

Leads HBM product reliability engineering, including reliability test-flow development, qualification execution, DPM reduction, failure analysis, root-cause resolution, process conversions, and manufacturing test optimization. Partners with fab, quality, technology development, design, and systems teams to improve yield, cost, cycle time, and product reliability. Mentors engineers, manages technical risks and priorities, and applies AI and machine learning to reliability data and qualification workflows.

Leads Micron’s global Photo MAP organization, overseeing photolithography, metrology, application, and process performance across semiconductor manufacturing sites. Develops technology roadmaps, improves productivity and overlay control, drives AI-enabled digital transformation, supports factory expansions, and standardizes best practices. Partners with manufacturing, technology development, process integration, and suppliers while building global teams, developing talent, managing strategic initiatives, and aligning manufacturing capabilities with business objectives.

Owns development, qualification, and deployment of advanced semiconductor metrology applications for 3D NAND process development. The role focuses on FIB and complementary techniques such as AFM, SEM, and WLI, while evaluating next-generation systems, developing technology roadmaps, partnering with suppliers, and applying AI, machine learning, and data analytics to improve defect detection, yield, reliability, and manufacturing readiness.

Lead regional commercialisation and deployment of AI-powered SME solutions across APAC. Act as APAC subject-matter expert on LLMs and agentic AI, translate customer needs into product requirements, run pilots and go-to-market strategies, and drive adoption through cross-functional collaboration with product, engineering, sales, and partners.

Join a front-office quantitative trading team to design and implement algorithmic execution strategies, back-test models and signals, build low-latency trading tools, and run real-time and post-trade transaction cost analysis to optimize execution.

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.

Leads AI transformation, governance, quality oversight, risk management, and responsible adoption across Pfizer Global Supply and QSEO. Establishes GxP-compliant AI lifecycle practices, inspection-readiness frameworks, governance forums, portfolio monitoring, inventory management, metrics, and reporting. Advises senior leaders on AI regulations, deployment risks, investment priorities, and compliance while leading cross-functional initiatives and influencing stakeholders across Quality, Digital, Operations, and R&D.

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.

Owns pre-silicon validation, simulation regression, post-silicon characterization, and simulation-to-silicon correlation for NAND test chip vehicles. Analyzes device and architecture sensitivities, defines test methodologies, leads root-cause investigations, and drives silicon learning across design, process, technology, and test teams. The role also develops reusable technical methods, influences cross-functional decisions, mentors engineers, and applies data analytics, machine learning, and AI-assisted tools.

Full-time internship focused on applying Python, statistical analysis, visualization, and introductory machine learning to semiconductor probe-test, electrical failure, and fabrication-process data. The intern will investigate yield behavior in advanced memory manufacturing, develop a multivariate analytics tool, identify potential yield-improvement opportunities, and present documented findings through a technical report and presentation.

Analyze semiconductor manufacturing data to identify yield detractors, reduce process variation, and improve device yield. Build data pipelines and automated processes using data from SQL databases, sensors, and fabrication tools. Apply statistical modeling, machine learning, and DOE analysis to solve production issues and support root cause investigations. Create dashboards and reports with visualization tools, collaborate with process engineering teams, and responsibly use AI-enabled tools to improve manufacturing outcomes.

Build and productionize machine learning models for semiconductor quality and manufacturing processes. Develop agentic AI, LLM, retrieval-augmented generation, tool-use, and memory capabilities for predictive quality workflows. Create maintainable analytical pipelines, optimize performance and token efficiency, and support testing, deployment, and monitoring. Communicate analytical findings to technical and non-technical stakeholders while applying AI tools responsibly.

Develop and deploy machine learning, statistical modeling, and predictive analytics solutions for semiconductor manufacturing and business operations. Analyze large datasets, build scalable data workflows, conduct exploratory and root-cause analysis, and partner with engineering and software teams to operationalize models. Lead analytics projects, communicate insights to technical and business stakeholders, mentor junior data scientists, and ensure responsible, secure, compliant use of AI and data.

Conduct silicon design validation for advanced NAND products through Verilog simulations, validation planning, laboratory measurements, and data analysis. The intern will use testers, oscilloscopes, probe stations, scripting, and engineering software to analyze validation data, generate technical reports, and prototype AI-enabled workflows for automated data collection, reporting, or anomaly detection.

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.

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.

Drive dry etch process and equipment performance using advanced data analytics, automation, machine learning, statistical modeling, and generative AI. Lead cross-functional initiatives integrating manufacturing, equipment, process, and business data. Develop scalable analytics solutions to improve productivity, tool utilization, cycle time, excursion response, process control, and manufacturing costs. Collaborate with suppliers and internal digital teams to evaluate and deploy AI technologies for semiconductor manufacturing.

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.

Develop and validate an AI-driven root cause analysis tool for semiconductor Chemical Vapor Deposition incident data. The intern will prepare and classify equipment alarms, process-control records, and human-written incident logs; train machine learning or generative AI models; identify recurring failure patterns; conduct correlation studies; and prototype Microsoft Teams integration for incident validation. The role includes data visualization, model validation, root cause analysis, and collaboration with cross-functional engineering experts.

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.

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 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.