Posted Today
MLOps/LLMOps Engineer
AI Summary
Responsible for operationalizing AI models, ensuring scalable, reliable, and automated deployment of ML and LLM solutions across environments. Responsibilities: - - Build and manage MLOps and LLMOps pipelines- Automate model deployment using CI/CD pipelines- Monitor model performance, drift, and retraining cycles- Manage model serving frameworks (e.g., vLLM, TGI, Ray Serve)- Implement experiment tracking and model versioning- Ensure governance, reproducibility, and compliance Requirements: - M
About this role
Responsible for operationalizing AI models, ensuring scalable, reliable, and automated deployment of ML and LLM solutions across environments.
Responsibilities: -
- Build and manage MLOps and LLMOps pipelines
- Automate model deployment using CI/CD pipelines
- Monitor model performance, drift, and retraining cycles
- Manage model serving frameworks (e.g., vLLM, TGI, Ray Serve)
- Implement experiment tracking and model versioning
- Ensure governance, reproducibility, and compliance
Requirements: -
Must have minimum 4 years of experience
Experience with Kubernetes, Docker
CI/CD tools (GitLab, Jenkins, Azure DevOps)
ML frameworks (TensorFlow, PyTorch)
Knowledge of LLM serving and optimization
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