MLOps Engineer

Seeking a highly skilled MLOps Engineer to develop and implement machine learning operations processes and infrastructure. As an MLOps Engineer, you will play a crucial role in developing and implementing machine learning operations processes and infrastructure to support data science initiatives.

Requirements

• Develop and maintain end-to-end machine learning operations (MLOps) pipelines for deploying, monitoring, and scaling machine learning models.
• Collaborate with data scientists, software engineers, and DevOps teams to ensure seamless integration of ML models into production systems.
• Design and implement automated testing frameworks for ML models to ensure accuracy, reliability, and performance.
• Optimize model deployment processes by leveraging containerization technologies such as Docker or Kubernetes.
• Implement continuous integration/continuous deployment (CI/CD) practices for ML model development lifecycle management.
• Monitor deployed ML models in production environments to identify performance issues or anomalies.
• Work closely with cross-functional teams to troubleshoot issues related to model performance or data quality in production systems.
• Stay up-to-date with the latest advancements in MLOps toolkits, frameworks, best practices, and industry trends.

Benefits

• Paid Time Off
• 401k Matching
• Retirement Plan