Top AI Jobs in Singapore

Support sourcing, diligencing, structuring and managing early-stage investments in deep tech and software/AI companies. Conduct market research, originate deal flow, perform commercial and technical due diligence, prepare investment memos, negotiate terms, and manage portfolio value creation alongside senior team members.

Conduct market research and source deals in digital economy sectors; perform commercial and financial due diligence; structure and negotiate investments; support portfolio company value creation and corporate strategy; prepare investment memos and present to the Investment Committee.

Provide hands-on production support and SRE for front-office trading platforms (single-dealer FX, digital FX, e-trading). Monitor system health, manage incidents, drive automation and observability, collaborate with platform and business stakeholders, and support cloud initiatives and rollouts.

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, build, and deploy end-to-end production AI applications for smart manufacturing: data pipelines, model training/inference, APIs, web/mobile front-ends, digital twins, robotics integration, containerized edge/cloud deployments, GPU inference optimization, Responsible AI, and 3D simulation validation.

The AI Adoption & Change Navigator drives AI solution adoption globally, provides regional coaching, customizes training for cultural relevance, and advocates for resources based on regional feedback.

Lead and support AIG's APAC privacy program: advise business units on privacy policies and laws, manage governance (DSARs, DPIAs, notices), develop policies, training and monitoring, coordinate incident and eDiscovery responses, and assess privacy impacts for new technologies and cloud/mobile implementations.

Develop machine learning, simulation, and optimization models to analyze manufacturing, equipment, and process data. Build scalable analytics products, dashboards, and automated workflows. Partner with cross-functional engineering teams to improve equipment efficiency, factory productivity, and drive operational excellence through data-driven insights and recommendations.

Lead design and delivery of end-to-end AI solutions for smart manufacturing, including data pipelines, ML/DL models, LLM and agentic AI integration, full-stack front-end/back-end apps, robotics and AMR integration, digital twin and 3D simulation, containerized cloud/edge deployment, CI/CD, observability, and team mentorship.

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

Lead AI-enabled cost transformation across procurement and manufacturing, build and operationalize a portfolio of AI/Generative AI use cases (spend, supplier, contract analytics), implement measurable savings and productivity improvements, embed solutions into workflows, manage cross-functional stakeholders, and scale data science and automation initiatives for value capture.

As an AI/Data Science Intern in NAND Device Engineering, you will develop AI-driven automation workflows, intelligent decision-support tools, and data pipelines to enhance engineering processes in NAND technology.

Lead and oversee MUFG's APAC sanctions compliance program, provide strategic advisory on sanctions/financial crime issues, manage regulatory engagement, drive program improvements and automation (including AI), oversee investigations, governance, remediation, and lead a regional team supporting enterprise-wide financial crime initiatives.

The internship involves hands-on learning in data analytics and machine learning. Interns will build data-driven models, perform statistical analyses, and communicate insights to improve process integration outcomes in semiconductor technology.

Lead independent oversight and advisory for enterprise cyber and digital risk across products, channels, cloud, AI, and third-party providers. Strengthen cyber resilience, influence governance, assess emerging technology risks, and ensure regulatory compliance across the Group.

Design, build, deploy, and support end-to-end AI applications for manufacturing: data pipelines, feature engineering, model training/inference, web UIs/APIs, containerized deployments, LLM/RAG integrations, MLOps, observability, and Responsible AI practices.

The Business Ecosystem Manager will drive ecosystem partnerships, enhance emerging technology adoption, and manage stakeholder relationships in the digital economy.

The Engineering Manager will define the team's vision, manage product roadmaps, mentor engineers, and drive technical strategies for digital transformation in the public sector.

The Visiting Professor will participate in teaching and research, supervise graduate students, and mentor junior faculty at NTU's College of Computing and Data Science.

The Visiting Professor will teach, conduct research, supervise graduate students, and mentor junior faculty while maintaining high scholarly standards and international visibility.

The AI Engineer will lead AI projects, train apprentices, develop AI technologies, manage recruitment, and support industry activities.

The Programme Manager will lead and manage projects related to tidal resources, supporting research, development, and deployment of energy solutions, while collaborating with stakeholders and providing mentorship to the research team.

Lead and execute Southeast Asia compliance strategy, advise senior management, manage regulatory engagement, oversee monitoring and policies, enable business growth through pragmatic compliance solutions, and modernize the function with tech and data-driven controls.

As a Principal Engineer, you'll lead CMP process development, optimization, and sustainability, while collaborating with teams to enhance performance and drive innovation in semiconductor fabrication.

The role involves developing AI-driven solutions for semiconductor engineering, focusing on GenAI systems, data pipelines, and machine learning models while collaborating with cross-functional teams.