Senior ML/AI Engineer with GCP

About the Position

We are looking for an ML/AI Engineer with solid knowledge of cloud technologies, Infrastructure as Code (IaC), CI/CD practices, and software engineering best practices, focused on designing, building, and operationalizing Generative AI based solutions.

About the Project

You will join a strategic initiative within the Emantto domain, contributing to the acceleration of the organization's AI portfolio across multiple business areas. This role combines ML/AI engineering with strong software engineering, cloud, and infrastructure expertise. You will build and operate Generative AI driven data products, support domain teams, and act as a facilitator for the Data & AI Platform.

Responsibilities

• Develop and deliver data products and AI/Generative AI solutions within domain teams.
• Act as a facilitator of the Data & AI Platform, enabling adoption and accelerating delivery across teams.
• Build, deploy, and operate Generative AI and Machine Learning models in scalable, production ready environments.
• Manage infrastructure related aspects of environments and AI/ML products, including observability, performance, and reliability.
• Contribute to CI/CD pipelines, Infrastructure as Code practices, and platform automation initiatives.
• Collaborate with cross functional teams, including Software Engineering, Data Engineering, MLOps, and DevOps teams, to maintain high engineering standards.
• Support experimentation frameworks and internal tools for Generative AI model development and evaluation.

Requirements

• Experience working with Google Cloud Platform (GCP).
• Experience with Terraform or other Infrastructure as Code tools.
• Strong proficiency in Python.
• Experience in backend engineering, including APIs and services, as well as Generative AI, Machine Learning, or MLOps technologies such as Airflow, MLflow, pipelines, and monitoring tools.
• Solid understanding of CI/CD practices, containerization using Docker, and software engineering best practices.
• Familiarity with model deployment, model serving, and operating Machine Learning and AI systems in production environments.

Nice to Have

• Experience with observability, incident response, or platform operations.