Senior Data DevOps Engineer (MLOps)

We are seeking a Senior Data DevOps Engineer (MLOps) with strong machine learning and Google Cloud Platform experience to design, develop, and implement continuous deployment pipelines for ML models.

Responsibilities

• Design, develop, and implement MLOps pipelines for the continuous deployment and integration of ML models
• Collaborate with data scientists to understand model requirements and optimize deployment processes
• Automate the training, testing, and deployment processes for machine learning models
• Monitor and maintain models, ensuring optimal performance, accuracy, and reliability
• Implement best practices for version control, model reproducibility, and governance
• Optimize machine learning pipelines for scalability, efficiency, and cost-effectiveness
• Troubleshoot and resolve issues related to model deployment and performance
• Ensure compliance with security and data privacy standards in all MLOps activities
• Stay up-to-date with the latest MLOps tools, technologies, and trends
• Provide support and guidance to other team members on MLOps practices and performance feedback

Requirements

• Bachelor's degree in Computer Science, Data Science, or a related field
• 3+ years of experience in MLOps, DevOps, or a related field
• Understanding of machine learning principles and model lifecycle management
• Proficiency in Python, with hands-on experience in TensorFlow, PyTorch, or Scikit-learn
• Knowledge of CI/CD pipelines, automation tools, and version control systems like Git
• Strong problem-solving skills and ability to troubleshoot complex issues
• Experience with monitoring tools and practices for model performance in production
• Ability to work collaboratively in cross-functional teams
• Experience with Google Cloud Platform and its respective machine learning services
• Familiarity with containerization and orchestration tools such as Composer and Kubernetes
• Knowledge of cloud data platform architecture, infrastructure, maintenance, and optimization