Required skills
Languages: French
Job description
Seeking a Senior MLOps Engineer with deep GCP expertise to industrialize, automate, and optimize the production of Machine Learning, AI, and GenAI projects within a Data Factory.
Project overview
🎯 Detailed description of the need
As part of strengthening a Data Factory within a large international group, we are looking for a Senior MLOps Engineer with in-depth expertise in Google Cloud Platform (GCP).
You will join a cross-functional technical team responsible for designing, industrializing, and maintaining Python, MLOps, and Cloud solutions for Data, AI, and business teams.
The objective of the mission is to make the deployment of Machine Learning, AI, and GenAI projects reliable, automated, and optimized, by leveraging GCP's managed services and MLOps best practices.
🔧 Your main missions
MLOps & AI Industrialization
GCP Architecture & Deployment
Python Development & Internal Tooling
Monitoring, Operations & FinOps
- Design, develop, and maintain MLOps pipelines with Vertex AI Pipelines.
- Industrialize the deployment and operation of Machine Learning and GenAI solutions.
- Automate ML workflows and contribute to the management of the model lifecycle.
- Implement MLOps best practices: CI/CD, automation, reproducibility, and monitoring.
- Deploy, configure, and administer environments on Google Cloud Platform.
- Design and maintain robust, scalable Cloud architectures adapted to AI/ML use cases.
- Ensure the deployment and operation of containerized applications via Cloud Run.
- Guarantee the reliability and maintainability of deployed infrastructures and services.
- Design, develop, and maintain internal Python libraries for technical teams.
- Structure reusable tools and facilitate their integration into Data/ML workflows.
- Contribute to the continuous improvement of tools and development practices.
- Implement and maintain technical monitoring and supervision systems.
- Ensure the stability and performance of solutions in production.
- Apply FinOps principles to optimize resource consumption and GCP costs.
Project details
- Start: flexible
- Remote: hybrid
- Location: Paris, France, FR
- Languages: French
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