Senior MLOps

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Requirements:

• 5+ years of experience in MLOps, DevOps, or related fields, focusing on deploying and managing LLMs.
• Proven experience with Hugging Face, MLFlow, and containerization technologies like Docker and Kubernetes.
• Strong experience with cloud platforms such as AWS, Azure, and GCP and infrastructure as code (Terraform).
• Proficiency in Python, with experience in ML libraries such as TensorFlow and PyTorch.
• Expertise in CI/CD pipelines, version control (Git), and orchestration tools.
• Familiarity with Generative AI and deploying models at scale.

Responsibilities:

• Develop and maintain scalable pipelines for deploying LLMs with low-latency inference.
• Implement monitoring frameworks to track performance and reliability of models in production.
• Optimize cloud and on-premise infrastructure for LLM operations.
• Collaborate with AI engineers and data scientists on project objectives.
• Document MLOps processes and provide training to team members.