Machine Learning Engineer

Job Summary :

We are seeking a talented and experienced Machine Learning Engineer to join our team, with a focus on delivering AI / ML solutions within the financial services industry. You will be responsible for designing, developing, and deploying machine learning models and platforms for fraud detection, AML, and core banking data transformation. The role requires strong technical expertise in ML engineering, experience in regulated environments, and the ability to work closely with business stakeholders.

Key Responsibilities :

• Design, implement, and oversee the deployment of middle-office fraud detection models, ensuring model performance, accuracy, and interpretability to support transparency for business and compliance stakeholders.
• Build and manage the AML platform for middle-office operations, including developing robust data transformation workflows to seamlessly integrate external and third-party data sources.
• Design, develop, and maintain data pipelines for core banking systems to support analytics and ML initiatives in large-scale FSI projects.
• Build and optimize machine learning pipelines using libraries such as scikit-learn, XGBoost, TensorFlow, or PyTorch.
• Implement monitoring and logging systems to track model performance in production, retrain models as needed to adapt to evolving data.
• Work with data scientists, data engineers, and compliance teams to translate regulatory and operational requirements into scalable ML solutions.
• Ensure all ML implementations follow data privacy, model governance, and auditability standards.
• Collaborate with DevOps teams to deploy models using ML Ops tools (e.g., MLflow, Airflow, Docker, Kubernetes).
• Write clear documentation and present model results and decisions to business stakeholders.

Required Skills & Qualifications :

Preferred Qualifications :

Please send your detailed resume in MS Word format to [email protected] with