MLOps Engineer

at  ITDS Business Consultants

JOIN US, AND MAKE AN IMPACT IN A GLOBAL TECH ENVIRONMENT!

Krakow-based opportunity with the possibility to work 80% remotely!
As a MLOps Engineer, you will be working for our client, a global financial institution. The client requires a skilled engineer to deploy and manage machine learning models using Google Cloud’s Vertex AI. Your responsibilities include collaborating closely with data engineering and software development teams to ensure efficient deployment and operation of data processing and analytics systems in production environments.

YOUR MAIN RESPONSIBILITIES:

• Deploying and managing machine learning models using Google Cloud’s Vertex AI
• Collaborating with data engineering and software development teams to ensure cost-effective and efficient deployment of data processing and analytics systems
• Developing and maintaining automated pipelines for model training, testing, and deployment
• Implementing version control and continuous integration/continuous deployment (CI/CD) processes for machine learning models
• Collaborating with DevOps teams to ensure the scalability and reliability of machine learning infrastructure
• Optimizing and monitoring model performance in production
• Implementing monitoring solutions to track model performance and data drift
• Responding to and troubleshooting issues related to deployed machine learning models
• Ensuring that machine learning operations comply with security and regulatory standards
• Implementing security measures to protect sensitive data used in machine learning models
• Documenting MLOps processes, configurations, and best practices
• Communicating effectively with cross-functional teams, including compliance analytics, software engineers, and stakeholders

YOU’RE IDEAL FOR THIS ROLE IF YOU HAVE:

• Experience deploying and managing machine learning models using Google Cloud’s Vertex AI
• Proficiency in developing and maintaining automated pipelines for model training, testing, and deployment
• Knowledge of version control and CI/CD processes for machine learning models
• Collaboration skills to work effectively with DevOps teams for infrastructure scalability and reliability
• Strong problem-solving abilities for monitoring and optimizing model performance in production