Senior Software Engineer, Machine Learning Platform

The role

You will build and scale the machine learning platform that powers risk decisioning. You will design data and model infrastructure, productionise machine learning workflows, and improve experimentation speed and quality.

What you will do

• Build and scale the machine learning platform that powers risk decisioning
• Design reliable data and model infrastructure
• 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

Required qualifications

• 5+ years of software engineering experience
• 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 (e.g., PyTorch, TensorFlow, JAX) and model training execution engines
• Strong proficiency in core programming languages such as Python, Java, or C++
• Experience with distributed orchestration and workflow management tools (e.g., Kubernetes, Ray, Kubeflow Pipelines, Airflow)
• Solid understanding of GPUs, including GPU architecture, hardware acceleration, and GPU-based training or inference optimization

Nice to have

• Experience with model acceleration frameworks and Large Language Models (LLMs)
• Proficiency in performance profiling and bottleneck identification using tools like NVIDIA Nsight Systems for training and inference optimization
• Experience with cloud platforms (e.g., AWS, GCP) and building large-scale, low-latency production machine learning infrastructure

About the company

Airwallex is an AI-native financial operating system for a real-time, intelligent economy. It provides financial infrastructure for over 675,000 businesses globally.