Senior ML Engineer – Risk & Data Integrity

Wise; Greater London; Hybrid; GBP 111,000 - 145,000; Full time

Benefits offered by this job

Wise Benefits

Job summary

Wise is seeking an IC3 Machine Learning Engineer to join the Risk ML and Intelligence team. You will focus on the label side, ensuring the integrity of labels for risk models and building robust audit processes. Work spans end-to-end ML, from training through deployment, with collaboration across Risk Intelligence, Data Engineering and Product teams.

The role emphasizes Python or Java, strong data skills, and developing scalable, reliable labeling systems in a fast-paced fintech environment.

Qualifications

• A STEM degree and strong mathematical/statistical fundamentals.
• Hands-on ML lifecycle experience: training, evaluation, deployment.
• Proficiency in Python or Java for data scripting and production engineering.
• Strong SQL skills and ability to build and analyze data pipelines.
• Experience with data visualization to understand statistical behavior.

Responsibilities

• Build and maintain the label integrity layer for Risk ML models.
• Define and monitor key data quality metrics and statistical fundamentals.
• Design automated audits to evaluate label quality over time.
• Contribute across end-to-end ML workflows from training to deployment.
• Collaborate with Risk Intelligence, Data Engineering and Product teams.

Skills

Python

Java

SQL

Statistical analysis

Data scripting

ML lifecycle

Education

STEM degree

Tools

Kafka

Graph Neural Networks

NLP

Job description

Wise is seeking an IC3 Machine Learning Engineer to join the Risk ML and Intelligence team. You will focus on the label side, ensuring the integrity of labels for risk models and building robust audit processes. Work spans end-to-end ML, from training through deployment, with collaboration across Risk Intelligence, Data Engineering and Product teams.

The role emphasizes Python or Java, strong data skills, and developing scalable, reliable labeling systems in a fast-paced fintech environment.