We are seeking an AI/ML Engineer to design, develop, and deploy production-grade ML models for insurance use cases. The role involves building predictive, NLP, and computer vision models, implementing end-to-end ML pipelines on AWS SageMaker, and ensuring scalable, secure, and compliant ML operations.
Key Responsibilities
- Develop models for claims prediction, fraud detection, underwriting risk, loss forecasting, and policy lapse.
- Implement NLP for claims and policy documents; computer vision for damage assessment.
- Build and maintain ML pipelines using SageMaker, Lambda, S3, ECR, ECS/EKS.
- Deploy real-time and batch inference endpoints; manage versioning, retraining, and monitoring (data/concept drift, bias).
- Integrate CI/CD for ML with CodePipeline/CodeBuild and maintain model governance and compliance documentation.
Technical Skills
- Python (Pandas, NumPy, Scikit-learn, PyTorch/TensorFlow), SQL.
- AWS SageMaker, Feature Store, IAM, VPC, S3, Lambda, ECS/EKS, Docker.
- API deployment (REST/gRPC); Infrastructure as Code (CloudFormation/Terraform).
Competencies
- Production ML deployment experience, problem-solving, and analytical skills.
- Ability to collaborate with actuarial, analytics, and DevOps teams.
- Focus on scalable, maintainable, and compliant ML solutions.