Machine Learning Engineer

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.

• Building, scaling, and maintaining the integrity layer of our label platform for Risk ML models.
• Defining, implementing, and monitoring statistical fundamentals and key quality metrics for data and labels.
• Designing automated audit processes to evaluate and monitor label quality over time.
• Working end-to-end on machine learning model training, evaluation, and pipeline deployment.
• Collaborating closely with cross-functional partners across Risk Intelligence, Data Engineering, and Product.

• A degree in STEM (Computer Science, Mathematics, Statistics, Physics, Chemistry, Electrical Engineering, or a related quantitative field).
• Strong mathematical and statistical fundamentals with a proven track record of applying statistical analysis to complex data environments.
• Hands-on experience working across model training, evaluation, and deployment (utilizing frameworks around Machine Learning, AI, Neural Networks, or NLP).
• Strong proficiency in Python or Java for data scripting and production engineering, alongside advanced SQL capability.
• Solid hands-on experience building static data pipelines, conducting deep-dive data analysis, and using data visualization tools to understand statistical behavior.
• Nice to Have: Proven success in competitive machine learning environments or platforms (e.g., Kaggle, KDD competitions, or Google Summer of Code / GSoC). Experience with specialized ML architectures such as Graph Neural Networks (GNNs), Support Vector Machines (SVM), Natural Language Processing (NLP), or Transformers/LSTMs. Familiarity with real-time streaming data pipelines (e.g., Kafka). Domain experience within Fintech, E-commerce, or fast-scaling tech companies.

• Starting salary: £111,000 - £145,000 + stock equity grants (RSUs vesting over 4 years) + benefits.