Work from Office
Full Time
Overview ML Engineer \u2013 BFSI Domain Responsibilities Build robust ML pipelines and automate model training, evaluation, and deployment. Optimize and tune models for financial time-series, pricing engines, and fraud detection. Collaborate with data scientists and data engineers to deploy scalable and secure ML models. Monitor model drift, data drift, and ensure models are retrained and updated as per regulatory norms. Implement CI/CD for ML and integrate with enterprise applications. Qualifications 3\u20135 years in ML engineering. Hands-on experience with MLOps and ML pipeline automation in BFSI context. Knowledge of security and compliance in ML lifecycle for finance. Essential skills Tech Stack Languages: Python ML Platforms: MLflow, Kubeflow MLOps Tools: Airflow, MLReef, Seldon Libraries: scikit-learn, XGBoost, LightGBM Cloud: GCP AI Platform Containerization: Docker, Kubernetes Experience 3\u20135 years in ML engineering.
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IT Services and IT Consulting
10001 Employees
113 Jobs
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