Responsibilities:
- Deploy and orchestrate ML/LLM workloads on AWS Bedrock or SageMaker.
- Integrate vector databases or retrieval components within AWS environments.
- Automate, orchestrate services, and integrate model runtime on AWS.
Requirements:
- Experience working with AWS services and deploying machine learning solutions.
Required Skills:
- Proficiency with AWS services used in ML pipelines: Lambda, API Gateway, ECR, S3, Step Functions.
- Ability to containerize and deploy ML components using Docker.
- Strong understanding of automation, service orchestration, and model runtime integration on AWS.
Preferred Skills:
- Experience with CloudWatch for observability.
- Integrating LLM/RAG pipelines with AWS managed services end to end.
- Familiarity with CI/CD tooling such as GitHub Actions, AWS CodeBuild/CodePipeline.
- Cost awareness when running model endpoints and retrieval workflows.
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