Senior ML Engineer: Label Quality for Risk Models (Equity)

Wise; City Of London; Sur place; GBP 111 000 - 145 000; Plein temps

Avantages offerts par ce poste

Stock equity grants

Wise Benefits

Résumé du poste

Wise is seeking an IC3 Machine Learning Engineer to join the Risk ML and Intelligence team. You will ensure label quality, monitoring, and robust audit processes to keep ML models trained on clean data.

Work with cross-functional partners across Risk Intelligence, Data Engineering, and Product. The role emphasizes Python or Java, ML lifecycle expertise, and building scalable data pipelines in a fintech environment.

Qualifications

• Education: A STEM degree (CS/Math/Stats/Physics/Engineering) or related field.
• Statistical Integrity: Strong mathematical and statistical fundamentals with experience applying stats to data environments.
• ML Lifecycle Expertise: Hands-on across model training, evaluation, and deployment with ML/AI frameworks.
• Programming Skills: Proficiency in Python or Java for data scripting and production engineering; solid SQL.
• Data Fundamentals: Building static data pipelines, deep-dive data analysis, and data visualization to understand behavior.

Responsabilités

• Build, scale, and maintain the label platform integrity layer for Risk ML models.
• Define, implement, and monitor statistical fundamentals and quality metrics for data and labels.
• Design automated audits to evaluate label quality over time.
• Contribute end-to-end to ML model training, evaluation, and pipeline deployment.
• Collaborate with Risk Intelligence, Data Engineering, and Product teams.

Connaissances

Python/Java

SQL

Data analysis

Statistical thinking

Formation

STEM degree (CS/Math/Stats/Physics/EE)

Outils

Kafka

ML frameworks (TensorFlow/PyTorch)

Description du poste

Wise is seeking an IC3 Machine Learning Engineer to join the Risk ML and Intelligence team. You will ensure label quality, monitoring, and robust audit processes to keep ML models trained on clean data.

Work with cross-functional partners across Risk Intelligence, Data Engineering, and Product. The role emphasizes Python or Java, ML lifecycle expertise, and building scalable data pipelines in a fintech environment.