AI/ML Engineer, DevOps

About this kind of role

What a AI/ML Engineer, DevOps usually does. The employer's own details are in the listing.

Typically does: Designs, develops, and deploys machine learning models and AI solutions. This role involves building and maintaining the infrastructure required for machine learning workflows, including data pipelines, model training, and deployment. They often collaborate with data scientists and software engineers to integrate AI capabilities into applications. Continuous monitoring and improvement of model performance and system reliability are also key responsibilities.

Tools and skills: Proficiency in programming languages like Python, experience with machine learning frameworks such as TensorFlow or PyTorch, and familiarity with DevOps tools like Docker, Kubernetes, and cloud platforms (AWS, Azure, or Google Cloud) are generally expected.

Good fit for: Individuals with a strong analytical background, a passion for automation, and the ability to bridge the gap between machine learning research and practical application often thrive in this role.