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