AI/ML Engineer with AWS SageMaker
Tasks
- Architect ML solutions using AWS SageMaker
- Automate ML CI CD using AWS CodePipeline
- Build ML training endpoints using AWS SageMaker
- Collaborate with stakeholders on ML platforms
- Deploy models and optimize inference performance
- Develop and deploy ML pipelines
- Evaluate models and manage model registry
- Implement MLOps governance and versioning
- Implement feature engineering and model training
- Monitor models in production
- Optimize cost and latency in production
Perks/Benefits
- Company-Paid Holidays
- Dental insurance
- Disability insurance
- Employee assistance program
- Life insurance
- Medical insurance
- Paid time off
- Retirement savings plan
- Vision insurance
Skills/Tech-stack
AWS Glue | AWS IAM | AWS Lambda | Amazon CloudWatch | Amazon ECS | Amazon EKS | Amazon Redshift | Amazon S3 | Amazon SageMaker | CI/CD | Classification | Deep learning | Docker | Feature Store | Kubernetes | Language Processing | MLOps | Machine Learning | Microservices | Model Monitoring | Model Registry | Natural Language | Natural Language Processing | PyTorch | Python | R | REST API | Regression | Sagemaker Pipelines | Scikit-learn | TensorFlow | Time Series | XGBoost
Education
N/A
Roles
AI | AI/ML Engineer | Engineer | Learning Engineer | ML Engineer | Machine Learning Engineer
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