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About the Role
Job Description
About your tasks:
- Develop and maintain CI/CD pipelines for deploying ML and LLM models in production, ensuring rapid and reliable model iteration.
- Optimize the deployment process for LLMs, considering cost, latency, and scalability constraints.
- Automate model retraining and redeployment processes to respond to changing data patterns.
- Set up and manage cloud and on-premise infrastructure for ML/LLM workloads on platforms such as AWS, GCP, or Azure.
- Work with containerization and orchestration tools (e.g., Docker, Kubernetes) to ensure scalable and resilient model deployment.
- Implement data versioning and validation processes to maintain data integrity throughout the ML lifecycle.
- Use tools like MLflow for tracking experiments, managing model versions, and maintaining reproducibility.
- Document MLOps/LLMOps practices and mentor team members on deployment best practices.
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