Cloud AI Engineer
Tasks
- Adhere to change management procedures
- Build train deploy machine learning models
- Collaborate to operationalize AI ML solutions
- Design implement ETL data workflows
- Develop maintain machine learning pipelines
- Document AI ML architecture and runbooks
- Implement model serving infrastructure
- Integrate large language models with guardrails
- Manage data lakes feature stores
- Monitor model performance data drift bias
- Optimize cloud resource usage and costs
- Prepare training datasets and ensure data quality
- Troubleshoot training failures and inference latency
Perks/Benefits
- N/A
Skills/Tech-stack
AWS Bedrock | AWS CloudFormation | AWS SageMaker | Ansible | Azure ML | Azure ML pipelines | Azure Machine Learning | Azure OpenAI | Azure OpenAI Service | Compliance | Data Governance | Data Science | Docker | Generative AI | Google Cloud | Google Cloud Vertex | Google Cloud Vertex AI | Infrastructure as Code | Kubeflow | Kubernetes | ML pipelines | MLOps | MLflow | Machine Learning | Model Governance | OCI Generative AI | OpenAI Service | Oracle Cloud | Oracle Cloud Infrastructure | Oracle Cloud Infrastructure Data Science | PyTorch | Python | RAG | Responsible AI | Retrieval-Augmented Generation | Sagemaker Pipelines | Scikit-learn | Spot instances | TensorFlow | Terraform | Vertex AI | “as-code”
Education
Associate Degree | Bachelor of Science | High School Diploma
Roles
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