Staff Machine Learning Engineer, Risk

Airwallex is the only unified payments and financial platform for global businesses. Powered by our unique combination of proprietary infrastructure and software, we empower over 150,000 businesses worldwide – including Brex, Rippling, Navan, Qantas, SHEIN and many more – with fully integrated solutions to manage everything from business accounts, payments, spend management and treasury, to embedded finance at a global scale.

Proudly founded in Melbourne, we have a team of over 1,800 of the brightest and most innovative people in tech across 26 offices around the globe. Valued at US$6.2 billion and backed by world-leading investors including Visa, Airtree, Blackbird, Sequoia, DST Global, Greenoaks, Salesforce Ventures, Lone Pine, and Square Peg, Airwallex is leading the charge in building the global payments and financial platform of the future. If you're ready to do the most ambitious work of your career, join us.

We hire successful builders with founder-like energy who want real impact, accelerated learning, and true ownership. You bring strong role-related expertise and sharp thinking, and you're motivated by our mission and operating principles. You move fast with good judgment, dig deep with curiosity, and make decisions from first principles, balancing speed and rigor.

You're humble and collaborative; turn zero‑to‑one ideas into real products, and you "get stuff done" end-to-end. You use AI to work smarter and solve problems faster. Here, you'll tackle complex, high‑visibility problems with exceptional teammates and grow your career as we build the future of global banking. If that sounds like you, let's build what's next.

The risk platform team at Airwallex is responsible for managing the risk for all the products at Airwallex, including GTPN, Payment, Issuing, Onboarding, and Account takeover. The risk landscape is constantly changing, and fraudsters are becoming increasingly sophisticated. We are at the forefront of innovation in risk management.

As a Staff Machine Learning engineer, you will tackle challenging machine learning problems in the international payment risk domain and help build industry-leading model systems. You will be responsible for implementing end-to-end ML solutions to address real business challenges and will be accountable for delivering business impact.

This role is based in "Singapore".

1. Analyze business requirements and translate them into machine learning problems

2. Work on data engineering, feature engineering, model training, and deployment

3. Identify issues and propose effective solutions through regular analysis

4. Develop machine learning platforms and tools to streamline ML workflows at Airwallex

5. Collaborate with cross-functional teams to apply models that solve business problems

We're looking for people who meet the minimum qualifications for this role. The preferred qualifications are great to have, but are not mandatory.

1. At least 8+ years experienced with common ML libraries, such as scikit-learn, TensorFlow, PyTorch, Keras, etc.

2. Bachelor's or above degree in Computer Science, Engineering, or a related technical field.

3. Proficient in coding language such as Python and SQL.

4. Experience in payment risk or international e-commerce risk is a plus.

5. Experience in applying LLMs to real-time risk management is a plus.

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.

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. If you are approached by someone claiming to represent Airwallex, please verify with our team.