Wise is a global technology company, building the best way to move and manage the world’s money.
Min fees. Max ease. Full speed.
Whether people and businesses are sending money to another country, spending abroad, or making and receiving international payments, Wise is on a mission to make their lives easier and save them money.
As part of our team, you will be helping us create an entirely new network for the world's money.
For everyone, everywhere.
More about our mission and what we offer.
Job DescriptionWise moves billions every year for millions of people and businesses across multiple countries and currencies. At that scale, financial crime is constantly evolving — from scams and account takeovers to money laundering and mule networks. Staying ahead of these threats means our automated controls and machine learning models need high-quality, timely insights.
The Risk Intelligence Platform team, part of Risk Machine Learning, builds the tools and automation that help Wise's FinCrime teams develop and improve those models. Our work covers areas such as model experimentation, bias and fairness, automated training-set maintenance, and threshold analysis.
Our main users are Data Scientists and Product Managers across Fraud Prevention, AML and Sanctions. We build the platform and tooling that removes repetitive Engineering work and enables these teams to focus on what matters most: identifying and preventing financial crime effectively at scale.
As part of the team, you'll work at the intersection of Backend Engineering, data and machine learning, solving complex Engineering problems that directly support Wise's FinCrime prevention capabilities.
QualificationsAs a Senior Backend Engineer, your job will be to provide guidance for Wise's data engineering and machine learning community, taking ownership of difficult technical problems.
Minimum requirements:
- Typically 7+ years of experience with Java (11+, 21+), although we care more about the depth and relevance of your experience than the number of years.
- Familiarity with Python
- Experience with batch or stream processing (preferably Apache Spark and Flink/Kafka streams)
- Familiarity with SQL and no-SQL (document) databases
- Experience with complex systems distributed across several microservices, Kafka, scattered data and ownership
- Hands-on knowledge of system integration patterns
- A strong product mindset and passion for user experience, you prioritise work with the customers in mind and drive data-driven decisions to fix customer pain-points
- Strong problem-solving skills to help refine problem statements and figure out how to solve them with the available data and from first principles
- High level of ownership, including identifying impactful problems to solve, getting buy-in from stakeholders and implementing the solution end-to-end
Nice to have:
- ML Engineering background, such as model training pipelines, automated label quality assurance, model experimentation frameworks
- Data Engineering background, such as experience with large-scale data pipelines, feature engineering and serving infrastructure, familiarity with graph algorithms and/or embedding techniques, awareness of data governance practices
- Experience with Apache Iceberg and/or Trino
What does success look like in this role?
- You’ll have onboarded and found your place through understanding your team and tribe vision and how you can contribute
- You’ll understand how our values can help you guide your work
- You’ll understand the reasons behind problematic payments and customer difficulties and how to go about solving them
- Understand our customers and the impact our product makes in their lives
- You'll be having a real world impact by building financial crime prevention systems which protect customers
- You’ll help us scale-up and build a world class money transfer product by finding solutions to our technical challenges and opportunities
For everyone, everywhere. We're people building money without borders — without judgement or prejudice, too. We believe teams are strongest when they are diverse, equitable and inclusive.
We're proud to have a truly international team, and we celebrate our differences.
Inclusive teams help us live our values and make sure every Wiser feels respected, empowered to contribute towards our mission and able to progress in their careers.
If you want to find out more about what it's like to work at Wise visit Wise.Jobs.
Keep up to date with life at Wise by following us on LinkedIn and Instagram.
Skills Required
- Typically 7+ years of experience with Java 11 or 21
- Familiarity with Python
- Experience with batch or stream processing
- Familiarity with Apache Spark and Flink or Kafka streams
- Familiarity with SQL and NoSQL document databases
- Experience with complex distributed systems across multiple microservices
- Experience with Kafka
- Hands-on knowledge of system integration patterns
- Strong product mindset and focus on user experience
- Strong problem-solving skills
- High level of ownership, including end-to-end implementation
- Machine learning engineering background, including model training pipelines, label quality assurance, or experimentation frameworks
- Data engineering background, including large-scale data pipelines, feature engineering, or serving infrastructure
- Familiarity with graph algorithms or embedding techniques
- Awareness of data governance practices
- Experience with Apache Iceberg or Trino
Wise Compensation & Benefits Highlights
-
Equity Value & Accessibility — Employee ownership through share awards is standard for permanent staff, and equity is described as a meaningful part of total compensation. This approach can make overall pay feel more competitive than base salary alone.
-
Leave & Time Off Breadth — Paid time off is highlighted as a strong part of the package, including specific praise from operations roles. Generous PTO contributes to a more favorable view of total rewards.
-
Healthcare Strength — Health insurance is called out positively alongside other core benefits. Strong coverage helps offset concerns about the cash components of pay.
Wise Insights
What We Do
Wise is a global technology company, building the best way to move and manage the world's money. With Wise Account and Wise Business, people and businesses can hold 40 currencies, move money between countries and spend money abroad. Large companies and banks use Wise technology too; an entirely new network for the world's money. Launched in 2011, Wise is one of the world’s fastest growing, profitable tech companies. In fiscal year 2025, Wise supported around 15.6 million people and businesses, processing over $185 billion in cross-border transactions and saving customers around $2.6 billion.
Why Work With Us
We’re truly global in who we are, how we work, and how we build. Everything we do is centred around creating a world of money that’s fast, easy, fair. And open to all. Everyone who works here owns a piece of Wise, from the work they do, to the stock they hold.
Gallery
.jpg)
_0.jpg)
_0.jpg)
.jpg)
.jpg)
.jpg)
.jpg)
Wise Offices
Hybrid Workspace
Employees engage in a combination of remote and on-site work.
We expect new joiners in the office most days to build connections and learn from colleagues for their first six months. After that, most Wisers split their working week between the office and home, typically coming in at least 12 times a month.
