Senior ML Platform Engineer – Risk & Real-Time AI

Airwallex; Singapore; On-site; SGD 180,000 - 260,000; Full time

Job summary

Airwallex, the AI-native financial operating system, is seeking a senior software engineer to scale the Risk Platform. Based in Singapore, you’ll build data pipelines, model training and deployment systems that protect billions of dollars moving through our platform daily.

You’ll collaborate with ML engineers, data scientists and product teams to deliver reliable, low-latency ML infrastructure, while owning the roadmap and pushing for rapid experimentation in a fast-paced fintech environment.

Qualifications

• Bachelor's or Master's degree in CS/Engineering or related field.
• 5+ years software engineering with 3+ years in model training infra, serving systems, or MLOps.
• Hands-on experience with modern deep learning frameworks (PyTorch, TensorFlow, JAX).
• Strong proficiency in Python, Java, or C++.
• Experience with distributed orchestration/workflow tools (Kubernetes, Ray, Kubeflow Pipelines, Airflow).
• Solid understanding of GPUs and GPU-accelerated training/inference.

Responsibilities

• Build and scale the ML platform powering risk decisioning across Airwallex.
• Design reliable data and model infrastructure, productionise ML workflows, and improve experimentation speed and decisioning quality.
• Collaborate with ML engineers, data scientists, product managers, and risk specialists to turn complex problems into dependable systems.

Skills

Deep learning

Python

Java/C++

Model training infra

ML Ops

Education

Bachelor's or Master's in CS/Engineering

Tools

PyTorch

TensorFlow

JAX

Kubernetes

Ray

Kubeflow Pipelines

Airflow

Job description

Airwallex, the AI-native financial operating system, is seeking a senior software engineer to scale the Risk Platform. Based in Singapore, you’ll build data pipelines, model training and deployment systems that protect billions of dollars moving through our platform daily.

You’ll collaborate with ML engineers, data scientists and product teams to deliver reliable, low-latency ML infrastructure, while owning the roadmap and pushing for rapid experimentation in a fast-paced fintech environment.