Machine Learning Engineer

Location: Hyderabad (Prorsum Technologies Work Location)

Experience: 24 Years

Employment Type: Full-Time

We are looking for a Machine Learning Engineer to develop, deploy, and maintain machine learning models for fintech applications. The ideal candidate will have hands-on experience in building predictive models for credit scoring, fraud detection, anomaly detection, and time-series forecasting.

• Design, develop, and deploy machine learning models for fintech use cases.
• Build and optimize models for credit risk assessment, fraud detection, and default prediction.
• Develop time-series forecasting solutions using advanced ML techniques.
• Work with large and complex datasets to extract meaningful insights.
• Collaborate with data engineers and business teams to implement scalable ML solutions.
• Monitor model performance and ensure continuous improvement.
• Implement MLOps best practices for model deployment and lifecycle management.

• Strong proficiency in Python.
• Hands-on experience with TensorFlow, PyTorch, and scikit-learn.
• Experience with LSTM/RNN models for time-series forecasting.
• Knowledge of credit scoring, anomaly detection, fraud detection, and P2P default modeling.
• Experience handling imbalanced datasets and model optimization techniques.
• Strong expertise in SQL/PostgreSQL.
• Experience with AWS SageMaker for model development and deployment.
• Familiarity with MLOps tools such as Docker and Kubeflow.

• Experience working in the FinTech or Banking domain.
• Understanding of model monitoring, explainability, and governance.
• Knowledge of cloud-based ML deployment and automation.

• Work on cutting-edge AI and ML solutions in the FinTech space.
• Opportunity to build impactful products used in real-world financial applications.
• Collaborative and innovation-driven work environment.
• Exposure to modern cloud and MLOps technologies.

Interested candidates can apply with their updated resume to : bhuvana@prorsum-tech.com