Source description
About the role
location : Mumbai (Thane) Exp :3to 5 yrs
NP Max 15 may joiner
3–5 years in ML engineering.
3–5 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.
Tech Stack
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.
Cloud: GCP AI Platform
Containerization: Docker, Kubernetes
Languages: Python
ML Platforms: MLflow, Kubeflow
MLOps Tools: Airflow, MLReef, Seldon
Libraries: scikit-learn, XGBoost, LightGBM
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