Senior Software Engineer, Machine Learning Platform

About the role

Airwallex, the AI-native financial operating system used by more than 675,000 businesses, is hiring a Senior Software Engineer for its Machine Learning Platform. You will build and scale the platform that powers risk decisioning across Airwallex, helping teams develop, deploy, monitor and improve models that protect every dollar moving through the platform. The role is based in Singapore, with five days a week in the office.

Key responsibilities

• Build and scale the machine learning platform that powers risk decisioning, helping teams develop, deploy, monitor and improve models.
• Design reliable data and model infrastructure and productionise machine learning workflows.
• Improve the speed and quality of experimentation and decisioning across the Risk Platform.
• Partner with machine learning engineers, data scientists, product managers and risk specialists to turn complex fraud and risk problems into dependable systems.

Required profile

• 5+ years of software engineering experience, with at least 3+ years focused on model training infrastructure, model serving systems or MLOps platforms.
• Bachelor's or Master's degree in Computer Science, Engineering or a related technical field.
• Hands-on experience with modern deep learning frameworks and model training execution engines.
• Strong proficiency in Python, Java or C++.
• Solid understanding of GPUs, including architecture, hardware acceleration and training/inference optimisation.
• Preferred: experience with model acceleration frameworks and LLMs, performance profiling with tools such as NVIDIA Nsight Systems, cloud platforms (AWS, GCP) and large-scale low-latency ML infrastructure.

The team builds the decisioning infrastructure between Airwallex and every dollar that moves through it, protecting 150,000+ businesses across 200+ countries and 90+ currencies. The role suits someone who owns the roadmap, thrives in ambiguity, enjoys cross-country collaboration and values in-person work five days a week.