Senior Software Engineer, Machine Learning Platform
Airwallex is hiring a Senior Software Engineer, Machine Learning Platform in Singapore, Singapore. Level rates it ; you can apply on Level.
AI in 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 us, directly or through our platform partners, to run their financial operations or build and monetize financial products of their own.
We started in Melbourne in 2015 to build the infrastructure global commerce runs on. We're the regulated backbone behind global payments: not by accident, but by design. A decade plus, 85+ licenses, and a financial infrastructure spanning North America, Europe, the Middle East, and Asia-Pacific.
We're co-headquartered in San Francisco and Singapore, with more than 2,300 people across 27 offices. We hire builders with founder-level energy, people who move fast with good judgment, dig in with real curiosity, and make calls from first principles rather than waiting to be told what to do. Read our operating principles to see it in full.
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, and improve the speed and quality of experimentation and decisioning across the Risk Platform.
You’ll partner closely with machine learning engineers, data scientists, product managers, and risk specialists to turn complex fraud and risk problems into dependable systems.
You’ll be based in Singapore and work from the office five days a week.
What we're looking for
Essentials
5+ years of software engineering experience, with 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.
Preferred
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.
You'll thrive here if
You’re comfortable owning the roadmap yourself.
You own the outcome and you don't wait for permission to fix what's broken.
You're comfortable with ambiguity. Give you a problem, not a prescription, and you'll run with it.
You enjoy working closely with people across multiple countries and time zones as part of one connected, global team, including flexing your hours occasionally to make that connection work.
You value in-person collaboration and are happy being in the office five days a week.
Learn more about your team
Risk Platform builds the decisioning infrastructure that sits between Airwallex and every dollar that moves through it, protecting 150,000+ businesses moving over US$260 billion a year across 200+ countries and 90+ currencies, and deciding, often in milliseconds, whether a new signup is real, a payment is safe, or a login is who they claim to be. The hard part is that fraud evolves fast, and every decision carries a two-sided cost: miss an attack and money is lost, over-block and a legitimate business can't get paid. We build this with streaming pipelines processing billions of events a day, graph databases exposing coordinated fraud rings, ML models scoring every transaction, and LLM agents that triage alerts. You don't need a fintech background, just an appetite for adversarial systems problems where the scoreboard is measured in dollars. If you want to help scale one of the world's fastest-growing financial platforms safely, this is the team.
Applicant Safety Policy: Fraud and Third-Party Recruiters
To protect you from recruitment scams, please be aware that Airwallex will not ask for bank details, sensitive ID numbers (i.e. passport), or any form of payment during the application or interview process. All official communication will come from an @airwallex.com email address. Please apply only through careers.airwallex.com or our official LinkedIn page.
Airwallex does not accept unsolicited resumes from search firms/recruiters. Airwallex will not pay any fees to search firms/recruiters if a candidate is submitted by a search firm/recruiter unless an agreement has been entered into with respect to specific open position(s). Search firms/recruiters submitting resumes to Airwallex on an unsolicited basis shall be deemed to accept this condition, regardless of any other provision to the contrary.
Equal opportunity
Airwallex is proud to be an equal opportunity employer. We value diversity and anyone seeking employment at Airwallex is considered based on merit, qualifications, competence and talent. We don’t regard color, religion, race, national origin, sexual orientation, ancestry, citizenship, sex, marital or family status, disability, gender, or any other legally protected status when making our hiring decisions. If you have a disability or special need that requires accommodation, please let us know.
How we rate this
Senior Software Engineer, Machine Learning Platform at Airwallex rates 90 out of 100 for how much of the daily work is AI. That makes it Builds AI (AI Level 4 of 4). The level is about AI in the job, not seniority.
Builds AI. The job is building AI systems.
- ●●●● Builds AI80 to 100
- ●●●○ Works on AI60 to 79
- ●●○○ Uses AI40 to 59
- ●○○○ Little AI0 to 39
Levels come from how often the tools, models and workflows of the role are named in the posting itself. Open the description and count.
Prepare for this job
A free preview built only from this posting: what it asks for, what you could be asked in an interview, and how to adjust your resume.
Skills and AI tools this role asks for
Questions you could be asked
- How do you decide when an AI agent can act on its own versus asking for approval first?
- How do you monitor a model once it's live, and how do you know it needs retraining?
- What are the limits of PyTorch that you've run into, and how did you work around them?
- What's a project where you used TensorFlow hands-on?
- Walk me through how you've used Jax in your day-to-day work.
Adapt your resume
- List these exact terms on your resume: AI agents, ML Ops, PyTorch, TensorFlow, and Jax. An applicant tracking system matches the wording, not the idea.
- Attach one line of real, concrete experience to at least one of them — a tool named with nothing behind it rarely survives a human read.
- Lead with what you built, trained or shipped — this role is judged on the AI system itself, not the tools around it.
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