Machine Learning / MLOps Architect

Role Overview

Design AI Architectures: You will design technical architecture solutions for AI and AI Generative systems, leveraging work frameworks and best practices from providers, or, relying on our extensive experience in engineering, to create robust and scalable AI systems that ensure optimal integration and performance. Lead Innovation: You will be a reference for implementing innovative AI and AI Generative solutions in business environments. Drive advanced platform architectures in the cloud that cover the entire data science lifecycle, with a focus on AIOps best practices using platforms like Azure Databricks, Azure Machine Learning, Amazon SageMaker, Google Vertex AI, and more, to develop cutting-edge solutions.

What You Will Do

Design AI Architectures, Lead Innovation, Drive advanced platform architectures in the cloud, Establish a solid foundation with a composable architecture of AI and ML systems, Define Strategies, Build Our Vision, Generate Impact

Why It Might Be a Fit

Technical degree: Computer Science, Telecommunications Engineering, Mathematics, Statistics, and/or similar. Professional experience: Experience in data architecture (either big data, AI... ) Theoretical and practical experience in the fundamentals of data science, solution lifecycles, and methodologies. Cloud architecture design: Experience in creating and building scalable AI system architectures for cloud platforms. Experience using the cloud in AI projects, with any of the following clouds: Azure, AWS, and Google Cloud.

Requirements

• Technical degree: Computer Science, Telecommunications Engineering, Mathematics, Statistics, and/or similar
• Professional experience: Experience in data architecture (either big data, AI... )
• Theoretical and practical experience in the fundamentals of data science, solution lifecycles, and methodologies
• Cloud architecture design: Experience in creating and building scalable AI system architectures for cloud platforms
• Experience using the cloud in AI projects, with any of the following clouds: Azure, AWS, and Google Cloud

Benefits

• Indefinite contract
• Telework or hybrid modality
• Intensive schedule in July and August
• Salary based on your education and experience
• Economic support for telework
• Access to training and certifications