MLOps (CLOSED)

Ensure the quality of the end-to-end lifecycle of our AI solutions. This includes everything from data preparation and model training to – POC and at scale – deployment, monitoring, and maintenance. This is in close collaboration with our AI Tech Lead and other team members, helping team to build and deliver AI-powered applications in a secure, efficient, and reliable manner. Such applications are designed to serve several use cases across distinct business areas.

Advise and guide the team on how to automate and optimize the deployment of AI-powered applications. Take the lead on establishing best practices and adopting the most suitable frameworks, tools and platforms for machine learning operations in the team.

Develop, deploy, maintain and continually improve AI-powered applications and ML pipelines, which might include multiple components, such as data ingestion and transformation, model training and serving, frontend interfaces, databases and APIs.

 Implement continuous integration and delivery (CI/CD) for our AI solutions

 Monitor model performance and data quality, and iterate on models in production.

 Collaborate with data engineers, data scientists and software engineers to make models, applications or use cases operational.

 Ensure the scalability and reliability of our AI and ML infrastructure.

 Ensure our practices keep up to date with MLOps standards.

 Actively share your knowledge with the team.