Senior ML Platform Engineer – Real-Time Risk Decisioning

Airwallex; United States; Hybrid; USD 150,000 - 210,000; Full time

Job summary

Airwallex is seeking an experienced Machine Learning Platform Engineer to build and scale the risk decisioning infrastructure. You will design data and model pipelines, train and deploy models, and optimize experimentation and inference performance.

You’ll collaborate with ML engineers, data scientists, product managers, and risk specialists across a global team, based in Seattle with a 3-day office presence weekly.

Qualifications

• 5+ years of software engineering experience with ML platforms.
• 3+ years focused on model training infra, serving, or MLOps.
• Bachelor’s or Master’s degree in Computer Science, Engineering, or related field.
• Hands-on with PyTorch, TensorFlow, or JAX; proficient in Python, Java, or C++.
• Experience with Kubernetes, Ray, Kubeflow Pipelines, Airflow.
• Solid GPU knowledge for training and inference optimization.

Responsibilities

• Build and scale the ML platform powering risk decisioning.
• Design data and model infrastructure; productionise ML workflows.
• Collaborate with ML engineers, data scientists, product managers, and risk specialists.

Skills

Software engineering

Model training infra

MLOps

Python

Java

C++

Kubernetes

Ray

Kubeflow Pipelines

Airflow

PyTorch

TensorFlow

JAX

GPU training

Education

Bachelor's or Master’s in CS/Engineering

Tools

NVIDIA Nsight Systems

AWS

GCP

Job description

Airwallex is seeking an experienced Machine Learning Platform Engineer to build and scale the risk decisioning infrastructure. You will design data and model pipelines, train and deploy models, and optimize experimentation and inference performance.

You’ll collaborate with ML engineers, data scientists, product managers, and risk specialists across a global team, based in Seattle with a 3-day office presence weekly.