Job Title : AI Engineer
Experience : 3+ yrs
Location : Remote options available
Role Overview :
We are seeking a skilled AI Engineer with 3–5 years of hands-on experience in designing, developing, and deploying AI / ML solutions in cloud environments. The ideal candidate will have strong proficiency in Python, experience with both Azure and AWS, and 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).