Ai Ml Engineer

Role & responsibilities

• Clean, analyse and prepare datasets; build ML feature and training pipelines.
• Develop, test and optimise ML models for fraud detection and risk scoring.
• Evaluate model performance using precision, recall and false-positive metrics.
• Monitor model performance, data drift and retrain models as required.
• Collaborate with backend and SDK engineers to deploy and integrate ML models.

Preferred candidate profile

• Hands-on experience with Python, NumPy, pandas and PyTorch or TensorFlow.
• Strong understanding of Machine Learning, neural networks and sequence modelling.
• Knowledge of SQL, EDA, data pipelines and imbalanced datasets.
• Experience in model evaluation, experimentation and version control.
• Proficiency in AI coding tools and ability to review and test generated code.

Good to Have: