Senior Software Engineer, Machine Learning Platform

Posted 4 Hours Ago
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Singapore, SGP
In-Office
Senior level
Artificial Intelligence • Fintech • Payments • Business Intelligence • Financial Services • Generative AI
Do the most ambitious work of your career. Airwallex is building the future of global banking.
The Role
Build and scale Airwallex’s machine learning platform for risk and fraud decisioning. Design data and model infrastructure, productionize training and serving workflows, improve experimentation, and optimize GPU-based training and inference. Partner with machine learning engineers, data scientists, product managers, and risk specialists to deliver reliable, low-latency systems. The role is based in Singapore and requires working from the office five days per week.
Summary Generated by Built In
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 forEssentials
  • 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.

Skills Required

  • 5+ years of software engineering experience
  • 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 PyTorch, TensorFlow, JAX, or similar deep learning frameworks and model training execution engines
  • Strong proficiency in Python, Java, or C++
  • Experience with Kubernetes, Ray, Kubeflow Pipelines, Airflow, or similar distributed orchestration and workflow management tools
  • Understanding of GPU architecture, hardware acceleration, and GPU-based training or inference optimization
  • Experience with model acceleration frameworks and Large Language Models
  • Proficiency with performance profiling and bottleneck identification using tools such as NVIDIA Nsight Systems
  • Experience with AWS, GCP, and large-scale, low-latency production machine learning infrastructure

What the Team is Saying

Airwallex Compensation & Benefits Highlights

  • Healthcare Strength — Available descriptions highlight medical, dental, vision, life, disability, and mental‑health/EAP coverage for U.S. employees, with Modern Health/Rula noted in eligible markets. Feedback suggests this comprehensive core health coverage is a standout element of the package.
  • Leave & Time Off Breadth — U.S. postings cite 20 vacation days plus 12 company holidays, alongside birthday leave and three volunteer days in some locations. These policies are portrayed as generous and complemented by flexible remote‑work options in approved locations.
  • Equity Value & Accessibility — Eligible employees may receive RSUs or stock options in many markets, with U.S. materials noting RSUs via Carta and performance‑based bonuses. Feedback suggests this ownership component is a key part of total compensation.

Airwallex Insights

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The Company
HQ: San Francisco, CA
2,300 Employees
Year Founded: 2015

What We Do

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 250,000+ businesses worldwide – including Brex, Navan, Qantas, SHEIN, McLaren 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 2,300 of the brightest and most innovative people in tech across 27 offices around the globe. Valued at US$11 billion and backed by world-leading investors including T. Rowe Price, Visa, Mastercard, Robinhood Ventures, Sequoia, Salesforce Ventures, DST Global, and Lone Pine Capital, 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.

Why Work With Us

Airwallex was founded by people told their idea was unreasonable, and we've hired that way ever since. We move fast, think globally, and give you ownership from day one. If you want to pioneer global finance at scale alongside the ambitious, let's talk.

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About our Teams

Airwallex Offices

Hybrid Workspace

Employees engage in a combination of remote and on-site work.

At a global level, we have a strong in-office culture. We’ve invested in world-class office space in hub cities around the world. We see the benefits of in-person conversation, mentoring, and knowledge-transfer as vital to our long-term success.

Typical time on-site: Not Specified
HQSan Francisco, US
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HQSingapore
Hong Kong, CN
Tokyo, JP
Sydney, AU
Bangalore, IN
Amsterdam, NL
Auckland, NZ
Kuala Lumpur, MY
Paris, FR
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London, UK
Melbourne, VIC
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New York City, US
Tel Aviv, IL
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Toronto, CA
Vilnius, LT
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