DevOps Engineer H/F - Levallois-Perret

- Design, industrialize, and maintain cloud environments for production, deployment, and scalability of AI models (Machine Learning and LLMs) on GCP and Azure. - Automate the CI/CD pipeline for the deployment of AI models (TensorFlow, PyTorch, Keras). - Set up optimized containers (Docker) and orchestrators (Kubernetes) to host AI models. - Ensure the availability, performance, and resilience of hosting infrastructures for AI use cases. - Monitor and supervise AI model performance in real-time using tools such as Nagios or Cloud Monitoring. - Implement logging and tracing solutions for AI infrastructures to ensure optimal traceability and quality. - Participate in optimizing AI models in production (fine-tuning, version management). - Integrate specialized observability tools for LLMs, such as Langfuse, to track and optimize their performance. - Orchestrate automated AI and data flows via solutions like Opcon. - Utilize DevOps tools (Terraform, Ansible, GitLab CI) to industrialize workflows integrating exposure of AI/LLMs via APIs. - Manage multi-cloud environments (GCP, Azure) with services like Kubernetes Engine, Functions, App Services, etc. - Implement emerging solutions for AI monitoring and automation (Flowize, N8N, Langfuse, etc.). - Collaborate with AI Data Engineers to integrate upstream data pipelines with deployed AI solutions. - Actively participate in technological watch around DevOps tools, cloud infrastructure, and AI advancements. - Conduct POCs on new approaches in management and automation of AI models to maximize their effectiveness.