Senior ML Platform Engineer — Real-Time Risk (Singapore)

Airwallex; Singapore; On-site; SGD 120,000 - 180,000; Full time

Job summary

Airwallex is seeking an experienced ML Platform Engineer to design, build, and optimize the core risk platform for real-time decisioning. You’ll focus on model training, tuning, evaluation, and high-performance inference using MLOps best practices.

You’ll collaborate with Data Science, Product, and Engineering teams across Asia-Pacific to deliver scalable ML capabilities, improve latency, and ensure robust, secure risk decisions for global customers.

Qualifications

• 5+ years software engineering, with 3+ years in model training/inference or MLOps.
• Bachelor's or Master’s in Computer Science, Engineering or related field.
• Hands-on with PyTorch, TensorFlow or JAX and model training engines.
• Strong programming in Python, Java or C++.
• Experience with Kubernetes, Ray, Kubeflow Pipelines, Airflow.

Responsibilities

• End-to-end model lifecycle management from training to serving.
• Design, build and scale ML infrastructure for risk models.
• Profile, optimize performance, latency and cost of training/inference workloads.
• Collaborate with Data Science, Product and Engineering to deliver scalable ML capabilities.

Skills

MLOps

Python

Distributed systems

GPU programming

PyTorch/TensorFlow/JAX

Education

Bachelor's or Master's in CS/Engineering

Tools

Kubernetes

Airflow

Kubeflow Pipelines

NVIDIA Nsight

Job description

Airwallex is seeking an experienced ML Platform Engineer to design, build, and optimize the core risk platform for real-time decisioning. You’ll focus on model training, tuning, evaluation, and high-performance inference using MLOps best practices.

You’ll collaborate with Data Science, Product, and Engineering teams across Asia-Pacific to deliver scalable ML capabilities, improve latency, and ensure robust, secure risk decisions for global customers.