Machine Learning Engineer
Core
Design, develop, deploy, and operationalize scalable, secure machine learning and AI solutions for business decision-making, risk management, and customer insights in a banking environment.
Role type
Machine Learning Engineer
Builds
Production-ready ML models, AI-driven solutions, and ML pipelines
Domain
Banking / Fintech / Risk Management
Deliverable
production ML models
Required skills
Python, SQL, machine learning algorithms, statistical modelling, feature engineering, model evaluation, MLOps practices, API development
Preferred skills
Scala, R, Java, C++, cloud platforms (AWS, Azure, GCP), MLOps tools (MLflow, Docker, Kubernetes, Airflow, Databricks, SageMaker, Azure ML, Vertex AI), banking/fintech domain experience
Technologies
Scikit-learn, TensorFlow, PyTorch, XGBoost, LightGBM, Pandas, NumPy
Responsibilities
Design, build, test, deploy, and maintain machine learning models; develop ML pipelines for training, testing, deployment, monitoring, and retraining; build APIs to expose ML models; perform feature engineering and data preparation; monitor model performance and data quality; ensure solutions align with governance standards; document model logic and deployment processes
Seniority
Mid-level, hands-on IC
