Senior Cloud AI/ML Engineer

4 days ago

kochi, India beBeeArtificialIntelligenceEngineer Full time

Job Overview:Seeking a skilled AI/ML Model Engineer with 3–5 years of experience in designing, developing, and deploying scalable AI/ML solutions in cloud environments.Design and implement efficient AI/ML models for banking applications (e.g., fraud detection, credit scoring, customer segmentation).Deploy and manage models in production using Azure ML and AWS SageMaker.Collaborate with data scientists, software engineers, and DevOps teams to operationalize ML workflows.Build and maintain CI/CD pipelines for ML model deployment and monitoring.Ensure compliance with data governance, security, and regulatory standards.Optimize model performance and resource usage in cloud environments.Key Responsibilities:Develop and implement machine learning algorithms for predictive modeling.Implement containerization and orchestration for efficient model deployment.Work closely with cross-functional teams to integrate ML models into banking applications.Stay up-to-date with industry trends and best practices in AI/ML engineering.Required Skills:Programming: Strong Python skills, including libraries like Pandas, NumPy, Scikit-learn, TensorFlow or PyTorch.Cloud Platforms: Hands-on experience with Azure ML, AWS SageMaker, and cloud-native services (e.g., Lambda, EC2, S3, Azure Functions).MLOps: Familiarity with ML lifecycle tools (MLflow, Kubeflow, Airflow), containerization (Docker), and orchestration (Kubernetes).Deployment: Experience deploying models as REST APIs or batch jobs in production environments.Version Control & CI/CD: Git, GitHub Actions, Azure DevOps, or AWS CodePipeline.Monitoring & Logging: Tools like Prometheus, Grafana, or cloud-native monitoring solutions.Preferred Qualifications:Experience in the banking or financial services domain.Knowledge of data privacy regulations (e.g., GDPR, PSD2).Exposure to generative AI or LLM fine-tuning is a plus.

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