Full-Time Data Driven | MLOps Engineer

Ensure the quality of the end-to-end lifecycle of our AI solutions: this includes everything from data preparation and model training to deployment, monitoring, and maintenance.

Close collaboration with the AI Tech Lead and other team members, helping the team to build and deliver AI-powered applications in a secure, efficient, and reliable manner.

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.

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.

Fluency in at least one OOP language (e.g., C# or Java).

Experience with common data science languages (e.g., Python or R).

Clear understanding of the machine learning project lifecycle.

Proficiency with open-source tools (e.g., Jenkins).

Experience with AWS Cloud Platform.

Proficiency in using query languages (e.g., SQL, Spark SQL).

Experience with container technologies like Docker and Kubernetes.

Experience with software build and release processes, unit testing, version control, Git.

A passion for ML/AI.

A collaborative and can-do attitude.

Excellent written and verbal communication skills, comfortable with audiences including product and engineering management.

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