Staff MLOps Engineer, LLMOps
Tasks
- Automate model versioning approval and compliance checks
- Build CI/CD workflows for model training evaluation deployment
- Capture traces for analysis and debugging
- Continuously evaluate and integrate AI tools
- Deploy and maintain LLM and agent workflows in production
- Design modular scalable AI infrastructure stack
- Drive AI reliability and governance
- Ensure data accuracy consistency and reliability for training and inference
- Implement offline and online evaluation for LLMs and agents
- Monitor cost latency and performance
- Optimize prompt response flows with real time data access
- Provide sandboxes dashboards and reproducible environments
Perks/Benefits
- N/A
Skills/Tech-stack
BentoML | CI/CD | Datadog | Docker | Drift Detection | Experiment tracking | Feature Stores | GitHub Actions | Human-in-the-loop | Inference Server | Kubernetes | Langchain | Langfuse | Llamaindex | MLflow | Model Serving | Model registries | Model versioning | Observability | OpenTelemetry | Prometheus | Prompt Optimization | Python | Regression testing | Terraform | The Loop | Triton Inference | Triton Inference Server | VLLM | Vector Databases
Education
N/A
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