Senior Software Engineer, Machine Learning Platform
Airwallex · US - Seattle
About this role
## About Airwallex Airwallex is the AI-native financial operating system for a real-time, intelligent economy. More than 675,000 businesses—including McLaren Racing, Qantas, SHEIN, and TikTok—use Airwallex to run financial operations or build and monetize financial products. We’re the regulated backbone behind global payments, with 85+ licenses and a financial infrastructure spanning North America, Europe, the Middle East, and Asia-Pacific. Co-headquartered in San Francisco and Singapore, with 2,700+ people across 27 offices. > Operating principles: https://www.airwallex.com/en-us/operating-principles --- ## How you’ll make impact You’ll build and scale the machine learning platform that powers risk decisioning across Airwallex—helping teams develop, deploy, monitor, and improve models that protect every dollar moving through our platform. You’ll: - 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 ML engineers, data scientists, product managers, and risk specialists to turn complex fraud and risk problems into dependable systems **Location / Work style:** Based in **Seattle**; **3 days/week in the office**. --- ## What we’re looking for ### Essentials - **5+ years** of software engineering experience, including **3+ years** in 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 **Python, Java, or C++** - Experience with distributed orchestration/workflow tools (e.g., **Kubernetes, Ray, Kubeflow Pipelines, Airflow**) - Solid understanding of **GPUs** (architecture, hardware acceleration, and GPU training/inference optimization) ### Preferred - Experience with model acceleration frameworks and **Large Language Models (LLMs)** - Proficiency in performance profiling and bottleneck identification (e.g., **NVIDIA Nsight Systems**) - Experience with cloud platforms (e.g., **AWS, GCP**) and building large-scale, low-latency production ML infrastructure --- ## You’ll thrive here if - You’re comfortable owning the roadmap and driving outcomes - You take initiative to fix what’s broken without waiting for permission - You’re comfortable with ambiguity (you’ll run with problems, not prescriptions) - You enjoy collaborating across multiple countries/time zones (with occasional flexing of hours) - You value in-person collaboration and are happy being in the office **five days a week** --- ## About the team (Risk Platform) Risk Platform builds the decisioning infrastructure between Airwallex and every dollar that moves through it—protecting **150,000+ businesses** processing **US$260B+** annually across **200+ countries** and **90+ currencies**. We decide, often in milliseconds, whether: - A new signup is real - A payment is safe - A login is who they claim to be Fraud evolves fast, and every decision has a two-sided cost (miss an attack vs. over-block legitimate businesses). We build this using: - Streaming pipelines processing billions of events/day - Graph databases exposing coordinated fraud rings - ML models scoring every transaction - LLM agents that triage alerts --- ## Applicant safety policy (Fraud & third-party r
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