11 hours ago
Budapest, HungarySenior
Responsibilities
- Build backend tools and automation that help FinCrime teams develop and improve machine-learning models.
- Develop capabilities for model experimentation, bias and fairness, automated training-set maintenance, and threshold analysis.
- Own difficult technical problems and provide guidance to Wise’s data engineering and machine-learning community.
- Work with batch or stream processing, distributed systems, scattered data, and system integration patterns.
- Identify impactful problems, gain stakeholder buy-in, and implement solutions end to end.
- Build financial-crime prevention systems supporting Fraud Prevention, AML, and Sanctions.
Requirements
- Typically 7+ years of relevant experience with Java 11+ or Java 21.
- Familiarity with Python.
- Experience with batch or stream processing, preferably Apache Spark and Flink/Kafka streams.
- Familiarity with SQL and NoSQL document databases.
- Experience with complex systems distributed across several microservices, Kafka, scattered data, and ownership.
- Hands-on knowledge of system integration patterns.
- Strong product mindset, user focus, problem-solving skills, and end-to-end ownership.
- Preferred qualifications include ML engineering experience with model training pipelines, label quality assurance, or experimentation frameworks.
- Preferred qualifications include data engineering experience with large-scale data pipelines, feature engineering and serving infrastructure, graph algorithms, embedding techniques, and data governance.
- Experience with Apache Iceberg and/or Trino is preferred.
Tech Stack
Categories
BackendData Engineering
About Wise
Wise builds a cross-border payments and multi-currency account used by individuals and businesses to send, receive, hold, and spend money in 40+ currencies. Revenue comes from transfer and account fees, card interchange, and enterprise partnerships via Wise Platform, which lets banks and large companies embed its international payments. Founded in 2011 as TransferWise, Wise is a London-headquartered public company.