AI DevOps / SRE Engineer

Description

As an AI DevOps / SRE Engineer, you will be pivotal in deploying, maintaining, and scaling our AI solutions, including LLMs and RAG systems. You will work closely with data scientists and software developers to ensure seamless integration and operational efficiency of our AI deployments. Your role will involve both classic DevOps tasks and innovative approaches to MLOps, ensuring high availability and optimal performance of our systems.

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Responsibilities

• Implement and maintain CI / CD pipelines for AI and machine learning projects, ensuring robust deployment strategies and continuous integration
• Monitor and ensure the reliability, availability, and performance of AI applications, particularly those involving LLMs and RAG
• Collaborate with AI research teams to operationalize machine learning models and systems efficiently
• Develop and enforce best practices for version control, configuration management, and testing of AI-driven software solutions
• Utilize MLOps tools such as Kubeflow, MLflow, or TensorFlow Extended (TFX) to streamline the machine learning lifecycle from experimentation to production
• Implement monitoring solutions that track both system metrics and model performance to facilitate proactive issue resolution
• Participate in on-call rotations to support the operational health of critical systems, employing SRE principles to meet service-level objectives (SLOs) and reduce downtime

Requirements

Nice to have

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