Senior MLOps Engineer

Responsibilities :

• Deploy and maintain machine learning models, pipelines, and workflows in production environment.
• Re-package (deployment process) ML models that have been developed in the non-production ML environment by ML Teams for deployment to the production ML environment.
• Perform the required MLOps engineering development to refactor the non-production ML model implementation to an "ML as Code" implementation.
• Create, manage, and execute ServiceNow change requests in accordance with the Elanco IT Change Management process to manage the deployment of new models.
• Build and maintain machine learning infrastructure that is scalable, reliable, and efficient.
• Provide expert data PaaS on Azure storage; big data platform services; server-less architectures; Azure SQL DB; NoSQL databases and secure, automated data pipelines.

What You Need to Succeed (minimum qualifications) :

What will give you a competitive edge (preferred qualifications) :

Additional Information :

Don’t meet every single requirement? Studies have shown underrecognized groups are less likely to apply to jobs unless they meet every single qualification. At Elanco we are dedicated to building a diverse and inclusive work environment. If you think you might be a good fit for a role but don't necessarily meet every requirement, we encourage you to apply. You may be the right candidate for this role or other roles!