Top AI & Machine Learning Jobs in Singapore

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.

Build and scale Airwallex’s machine learning platform for risk and fraud decisioning. Design data and model infrastructure, productionize training and serving workflows, improve experimentation, and optimize GPU-based training and inference. Partner with machine learning engineers, data scientists, product managers, and risk specialists to deliver reliable, low-latency systems. The role is based in Singapore and requires working from the office five days per week.

Lead analytical design for regulatory reporting and risk-compliance data infrastructure. Define data logic, models, validation frameworks, automated testing, and QA processes; investigate anomalies and audit findings; partner with compliance, finance, data, and engineering teams; shape scalable reporting platforms; and mentor analysts and data scientists.

Lead analytics and data design for regulatory reporting and financial crime compliance. Build data models, validation frameworks, automated testing, QA playbooks, and self-service analytics in partnership with Compliance, Finance, DataOps, and Engineering. Investigate anomalies and audit findings, identify root causes, shape risk analytics platforms, and promote analytical rigor and documentation across global teams.

Lead data science strategy for AML and financial crime risk controls. Develop AI-powered screening, entity resolution, graph and network intelligence, anomaly detection, transaction monitoring, and proactive discovery of emerging threats. Partner with Product, Engineering, Compliance, and Operations to deliver scalable production controls, influence the roadmap, establish reusable frameworks, and mentor data scientists.

Lead the Kai generative AI engineering team by defining architecture, building reliable agentic systems, and delivering trusted AI products. Manage and mentor AI, backend, and frontend engineers while driving evaluation, safety, observability, scalability, security, and operational readiness. Partner with Product, Design, Data, Security, Infrastructure, and domain teams to translate business needs into secure customer experiences and reusable AI platforms.

Design and deploy AI agents for payment processing and risk management. Translate business problems into production AI solutions using orchestration frameworks, prompting, RAG, and fine-tuning. Optimize agent reasoning, tool use, and workflow automation, integrate systems with secure backend and frontend platforms, and build evaluation, monitoring, and governance frameworks. The role requires production applied AI/ML experience, strong Python and ML framework skills, and the ability to balance innovation with reliability, scalability, and compliance.

Lead credit risk analytics for business lending: monitor portfolio performance, identify emerging risks, support portfolio-level credit strategies, prepare reports and dashboards, collaborate with operations and product, contribute to stress testing, regulatory reporting, and governance.

Design, build, and operate AI agents that automate SRE, DevOps, and DBA workflows across global infrastructure. Develop safe agent architectures with planning, reasoning, tool execution, error recovery, evaluation, and human escalation. Integrate agents with Kubernetes, Terraform, cloud APIs, databases, monitoring platforms, and CI/CD systems. Collaborate with infrastructure teams to identify automation opportunities and shape Airwallex’s infrastructure AI strategy.

Design and deploy real-time ML models and credit risk frameworks to detect fraud and assess merchant lending risk. Translate business needs into scalable analytics, monitoring, and decision-support tools. Partner with product, engineering, and operations to productionize models and improve risk visibility and decision quality.