Senior ML Platform Engineer II

Responsibilities

• Design and build a greenfield, declarative training pipeline to standardize model training for data scientists
• Develop model packaging and serving abstractions to provide a unified interface for various model architectures
• Implement a robust model evaluation framework featuring standardized metrics and automated validation gates
• Build comprehensive model monitoring systems, including drift detection, performance alerts, and automated retraining triggers
• Own the integration layer with Wise's central ML infrastructure to ensure seamless lifecycle tooling
• Drive data science productivity by shifting focus from operational maintenance to detection performance

Requirements

• Proven experience building production-grade ML platform infrastructure (training pipelines, serving, or monitoring)
• Strong software engineering fundamentals with proficiency in Python, Kotlin/Java, and SQL
• Hands-on experience with ML orchestration tools such as Airflow or Kubeflow
• Deep understanding of model registries (e.g., MLflow) and container-based deployment
• Comprehensive knowledge of the end-to-end ML lifecycle, from data ingestion to monitoring
• A product-oriented mindset focused on building highly adoptable internal tools for data scientists

Preferred Qualifications

• Experience with large-scale model serving, including latency optimization and ONNX packaging
• Background in FinCrime, fraud detection, AML, or other highly regulated environments
• Experience implementing model governance and audit trails for regulatory compliance
• Track record of successfully migrating teams from manual ML workflows to automated platform-based approaches

Benefits

• Competitive salary: £111,000 - £145,000 + RSUs
• Flexible working environment

About the Company

Wise is a global technology company on a mission to make moving and managing money borderless, instant, and free. We are building a new network for the world's money to save people time and money on international payments.