About MoonPay
Hi, we’re MoonPay. We’re here to onboard the world to the decentralized economy by making digital money move as universally and effortlessly as the internet.
Why?
Because crypto, stablecoins and blockchain aren’t just technologies. They’re tools for global financial empowerment. They give people and businesses more control over their money, their digital assets, and their future, opening access to legacy financial systems that have been out of reach for many.
What we do
MoonPay is a unified payments platform for digital currency. We make it easy for anyone, anywhere, to buy, sell, swap and pay in digital currencies as easy as sending an email. That simplicity is intentional, our focus is reducing complexity so people can participate confidently, without needing to be crypto experts. We power the entire flow between fiat and crypto end to end, with compliance, identity checks, fraud prevention, and settlement all built in. This end-to-end approach reflects how we work internally: with accountability, rigor, and trust built into everything we ship.
Proven at scale
Trusted by over 30 million customers and over 500 ecosystem partners, our secure, enterprise-grade platform is driving mainstream crypto adoption worldwide. Behind those numbers are millions of real people and organizations relying on MoonPay every day.
We collaborate with innovative brands and projects to build secure, scalable solutions for a blockchain-powered future. This is an opportunity to help shape systems, not just scale them. And we’re committed to doing it right. Fully licensed in the U.S. and regulated across the UK, EU, Canada, and Australia, because trust and compliance are non-negotiable.
But we’re just getting started. We’ve launched a consumer app that makes crypto accessible, intuitive, and usable for everyone, and it’s growing fast. We’re iterating every day to make it the best it can be.
If you believe financial freedom should be for everyone. If you believe in building a fairer, more open financial system - we want you with us. To build systems that benefit all, we need contributions from all, regardless of background.
Come build the future of payments and the decentralized economy with MoonPay. Let’s make financial freedom and autonomy the new normal.
About the Opportunity:
In this role, you will design, build, and deploy machine learning systems to detect and prevent fraudulent activity across our crypto products, helping protect our customers and platform in real time.
You will join the Machine Learning team and collaborate closely with Product, Data, Engineering, and Operations to deliver high-impact ML solutions end-to-end.
Your work will directly improve fraud detection, strengthen customer trust, and influence key business metrics. This role is well suited to someone who enjoys owning problems end-to-end, thrives in fast-paced environments, and is motivated by solving complex, high-stakes challenges with real-world impact.
What you will do:
- Build and deploy machine learning models to evaluate transactions and customer behaviour in real-time and batch environments
- Develop and iterate on fraud detection models through hypothesis-driven experimentation across multiple products
- Own the full ML lifecycle from feature engineering and model development through to deployment, monitoring, and continuous improvement
- Design and build features from large-scale datasets, including real-time feature generation
- Apply advanced modelling techniques (e.g. gradient boosting, deep learning) and take them to production
- Collaborate cross-functionally to ship models and ensure they deliver measurable impact
- Improve ML infrastructure through pipelines, automation, and internal tooling
- Monitor and evolve models to ensure reliability, performance, and robustness over time
USA Salary Range 191,737$ - 235,214$ /year
About You:
Must have experience and skills
Proven track record of building, deploying, and maintaining machine learning models in production, ideally in fraud, payments, or other risk-focused domains
Ability to frame problems, develop hypotheses, and iterate on models through structured experimentation
Strong understanding of the end-to-end ML lifecycle, including monitoring and iteration in production
Experience designing and operating real-time or high throughput data systems (e.g. think Apache Beam, Apache Spark, BigQuery, or similar)
Strong problem-solving skills and ability to operate autonomously in a fast-moving environment
Nice to have experience
- Familiarity with modern ML infrastructure and orchestration tools (e.g. Kubeflow, Airflow, Vertex AI or similar)
- Experience with cloud platforms (GCP, AWS, or Azure) and distributed systems
- Background in time series data, adversarial modelling, or counterfactual analysis
Bonus points
- Experience with deep learning frameworks (e.g. PyTorch)
- Contributions to ML tooling, internal platforms, or open-source projects
