Top Machine Learning Jobs in Singapore

Develop and deploy advanced machine learning models across asset classes, focusing on deep learning, sequence/time-series modeling, NLP/LLMs, pre-training, fine-tuning, and reinforcement learning. Design and optimize models for performance, scalability, and robustness to model price formation, market behavior, and risk while collaborating with researchers, engineers, and traders.

Manage requests for new ServiceNow reports and dashboards, resolve dashboard/reporting incidents, train users on dashboards, build executive KPIs and scorecards, engage stakeholders to gather requirements, and apply AI/Generative AI for reporting automation and insights.

Develop uncertainty-aware algorithms and reproducible Python pipelines to infer and map underground fiber-optic cable routes by fusing DAS-derived signals with GNSS, inertial, imagery and map datasets; conduct field data collection, validate inferred routes, quantify spatial uncertainty, and prepare publications, reports, and collaborative research deliverables.

As a Research Scientist, you will lead innovative AI research, design experiments, publish findings, and collaborate on integration into products.

As a Data Scientist, you will translate business problems into data analytics solutions, manage the ML lifecycle, and improve driver incentives through statistical analysis.

The Head of Data Science will lead the data science team across Southeast Asia, focusing on credit risk model development, strategic collaboration, and shaping the machine learning roadmap.

Lead engineering teams to design, deliver, and operate cloud-native, scalable compliance, surveillance, and supervision platforms. Drive architecture, API/event-driven microservices, big-data and AI-enabled analytics, vendor integrations, regulatory controls, and Agile delivery while partnering with Compliance, Risk, Data, and Business stakeholders.

The Responsible AI Specialist will develop AI governance standards, conduct risk assessments, engage stakeholders, and promote ethical AI practices across UOB.

The AI Product Owner will drive AI integration into the Razer Gold Digital Wallet, optimizing operations and enhancing user experience through innovative features and data-driven insights across teams.

As a Principal AI Engineer, you will lead the architecture and deployment of large-scale conversational chatbot systems, optimizing their performance for enterprise and consumer use cases.

The role involves maintaining equipment readiness, performing preventive maintenance, troubleshooting equipment, and supporting safety practices in an engineering environment.

The Data Science Intern analyzes large datasets, uses machine learning and analytics to solve gaming challenges, and collaborates with teams to drive business strategies.

Lead regional sales operations planning and execution—territory, quota, segmentation, employee data, and Blueprint. Drive automation and AI adoption, deliver actionable insights and standardized reporting, strengthen governance, and partner cross-functionally to improve coverage, quota predictability, and operational efficiency.

Build and deploy data processing pipelines (batch and real-time), clean and extract information, calibrate fraud detection models, collaborate with clients, and conduct R&D on machine learning, NLP, and image analysis to drive product innovation.

Summer-to-winter internship embedding with engineering and quant teams to build trading infrastructure, connect new venues and blockchains, optimise algos, and develop statistical/machine learning models to identify market inefficiencies and support live trading.

The role involves developing AI strategies for various business functions, implementing POCs, collaborating with teams on AI solutions, and ensuring compliance with AI governance.

Lead the development of regional marketing strategy and digital transformation for group retail, ensuring governance and efficient processes across multiple markets.

The role involves leading the development of data and analytics solutions, focusing on machine learning and NLP to improve financial decision-making.

Conduct independent research on computer vision and machine learning: process data, develop and evaluate algorithms, author peer-reviewed papers, engineer research software, design experiments, analyse results, propose new projects and funding ideas, and manage research-related tasks.

Lead data analysis and automation for Compliance reporting, building ETL and analytics solutions with Python, SQL and Starburst; create Power BI dashboards; ensure BCBS 239 and data governance compliance; act as Compliance Data Steward; collaborate with stakeholders to improve data processes and conduct business impact assessments.

Lead data quality monitoring and investigations for the One Finance Platform, driving root-cause resolution, stakeholder engagement, and implementation of scalable, automated, and AI-driven solutions to improve data integrity and operational efficiency across finance systems.

Own commercial strategy and operations for enterprise pharma and AI accounts: drive pilots-to-revenue, account expansion, pipeline management, pricing, forecasting, and deal strategy. Build cross-functional relationships, push deals through legal/procurement/IT, act as CEO counterpart to shape strategy and product roadmap, and be highly present in person with customers and at conferences.

Lead product vision and discovery for a genomics-driven diagnostic and personalization platform. Validate hypotheses with patients, clinicians, and partners; translate research into product specs; coordinate labs and data providers; partner with engineers and researchers to build AI prototypes; shape data, regulatory, and GTM strategy while making core product and architectural decisions.

Build core components of a diagnostic and personalization platform: backend data pipelines, frontends, services for genomic data ingestion, ML model integration, APIs, and cloud infrastructure. Collaborate with product and ML teams, iterate on prototypes and MVPs, and make architectural decisions supporting scalability and reliability.

Conduct interdisciplinary research on contactless sensing and sustainable living. Design wireless sensing systems, develop AI/ML and signal-processing algorithms, validate systems in lab and field, analyze large-scale sensing data, publish research, collaborate with partners, mentor students, and present findings at conferences.