AI Innovator

1 day ago

Kolhapur, India beBeeArtificial Full time

**Job Title:** AI EngineerAre you looking for a career opportunity that combines cutting-edge technology with innovative problem-solving? Look no further As an AI Engineer, you will be at the forefront of developing and deploying artificial intelligence solutions to drive business success.With 3-5 years of experience in designing, developing, and deploying AI/ML solutions in cloud environments, you will have a strong foundation in Python programming languages, including libraries like Pandas, NumPy, Scikit-learn, TensorFlow or PyTorch. You will also have hands-on experience with both Azure and AWS, as well as a solid understanding of MLOps practices.Key Responsibilities:Design and implement scalable 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.Document processes, models, and deployment strategies for internal knowledge sharing.**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. (Certifications in Azure or AWS) (e.g., Azure AI Engineer Associate, AWS Certified Machine Learning).

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