Opportunity Description
The MLOps Engineer II will independently design, implement, and manage the automation and streamlining of the machine learning lifecycle, ensuring reliable, efficient, and scalable deployment and monitoring of models. This role requires a solid understanding of DevOps practices, cloud technologies, and machine learning frameworks, with the ability to bridge the gap between data science and operations effectively.
Focus: Independent automation of ML pipelines, deployment strategies, and monitoring in production.
The difference you will make:
- Independently design and implement CI/CD pipelines for machine learning models.
- Automate the process of model training, validation, testing, and deployment using relevant tools.
- Develop and maintain automated testing frameworks for machine learning models.
- Develop and manage various model deployment strategies (e.g., A/B testing, canary deployments).