MID Google Cloud ML / Data Engineer

Position Overview:

We are seeking an experienced Google Cloud ML / Data Engineer to join our team, specializing in building and deploying advanced machine learning solutions on Google Cloud. This role will focus on designing, implementing, and optimizing ML models and data pipelines using Vertex AI and Google Cloud tools, as well as collaborating within Agile teams to deliver high-impact data-driven projects.

Key Responsibilities:

• Design, build, and deploy machine learning models and data pipelines on Google Cloud Platform using Vertex AI (pipelines, models & endpoints, feature store).
• Implement CI/CD pipelines for ML models using Azure DevOps and Terraform for infrastructure automation.
• Collaborate with data scientists and software engineers to implement scalable ML solutions that meet organizational needs.
• Drive the implementation of machine learning capabilities in client organizations, guiding them through the process of adopting and optimizing ML infrastructure.
• Maintain robust and reliable machine learning systems in production environments, ensuring model performance and scalability.
• Work closely with cross-functional Agile teams to ensure effective communication and collaboration throughout the development process.

Required Skills & Experience:

• Proven experience in Google Cloud services, particularly as a Professional Data Engineer and/or Professional Machine Learning Engineer.
• Strong proficiency in Python for developing and deploying machine learning models.
• Hands-on experience with Vertex AI for building ML models, managing endpoints, and using feature stores.
• Expertise in CI/CD pipelines with Azure DevOps for model versioning, testing, and deployment.
• Experience with Terraform for infrastructure automation and management.
• Excellent communication and collaboration skills, with the ability to work effectively in Agile teams.

Nice to Have:

• Experience with Google Cloud Dataflow for processing large-scale datasets.
• Knowledge of BigQuery for data storage, querying, and analysis.
• Familiarity with Composer for orchestrating data workflows.