Senior Engineer - LLMOps & MLOps
Telecommuter TN, United States
R
USD 120K-189K (estimate) Senior-level Full Time
Tasks
- Automate feature stores and feature engineering pipelines
- Build and maintain automated CI/CD pipelines
- Build and maintain continuous training pipelines
- Configure IAM roles and network security settings
- Deploy LLM RAG applications and ML models
- Harden security and compliance using automated scanning and guardrails
- Implement RAG infrastructure
- Implement automated LLM evaluation frameworks
- Implement automated model validation
- Implement prompt and model versioning
- Ingest and move legacy data to cloud
- Integrate analytics platforms with production models
- Manage AI resources using infrastructure as code
- Manage vector databases
- Optimize scalable inference endpoints
- Optimize semantic indexes
- Set up monitoring for model drift hallucinations latency and token usage
Perks/Benefits
Skills/Tech-stack
AI Search | AWS | AWS Step Functions | Airflow | Amazon Bedrock | Arize Phoenix | Azure | Azure AI | Azure AI Search | Azure OpenAI | CI/CD | Docker | Drift Detection | IAM | Kubeflow | Kubernetes | LLMOps | Langsmith | MLOps | Machine Learning | Meteor | Model Drift | Model Drift Detection | Model Evaluation | Monitoring | Observability | OpenAI | OpenSearch | Pinecone | Prompt injection | PromptOps | PySpark | Python | RAG | ROUGE | ROUGE L | Retrieval-Augmented Generation | SQL | Security guardrails | Semantic indexing | Serverless | Step Functions | Terraform | VPC | Vector Databases | WhyLabs
Education
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