Machine Learning Engineer

• Empowering ML Engineers by providing tools and infrastructure that enhance their productivity while adapting to their specific needs.
• Accelerating time-to-market for the first production-ready versions of ML products by ensuring seamless integration, proper service connections, and access to data and resources.
• Ensuring ML Engineers maintain control over their models in production, allowing them to monitor, troubleshoot, iterate quickly, and refine models and feature engineering logic.
• Facilitating large-scale ML experimentation by providing robust, reproducible, and scalable test environments for data science projects, enabling both qualitative experimentation (internal tests and demos) and quantitative experimentation (A/B testing in production).
• Owning the industrialization and deployment (CI/CD) of ML models , ensuring their reliability, scalability, and performance through advanced MLOps practices.
• Managing model operations and maintenance , guaranteeing optimal performance, monitoring, and continuous improvements in production.

Senior MLOps Engineer

Senior Data AI Engineer

Internship – MLOps, Generative AI

AI Engineer