ML Ops Engineer – Remote

For our key client, we are looking for an ML Ops Engineer to join one of the most strategic projects within the company.

Collaborate with data scientists and engineers to ensure ML models can be integrated seamlessly into the production environment
Design and implement infrastructure and tooling for deploying and scaling machine learning models in production for Data Science teams – with the final goal of making deployment and OPs as easy as possible for the user
Develop and maintain automated testing and deployment pipelines to streamline the release process
Provide guidance and support to Data Science departments on infrastructure and deployment processes
Establish and enforce best practices and standard operating procedures for infrastructure and deployment processes across the organization
Conceptualize and implement monitoring of production systems to identify and resolve issues in a timely manner
Implement and maintain system and application-level security practices
Continuous quality control and further development of Data Science solutions
Automate infrastructure provisioning and management using tools such as Terraform and Ansible
Implement and maintain CI/CD pipeline templates for ML models using tools such as Jenkins
Develop and maintain documentation and standard operating procedures for infrastructure and deployment processes of Machine Learning applications across the organization
Be the main driver of Machine Learning Automation within the company

minimum of 5 years of experience with DevOps and Data Engineering/Science/Machine Learning.
Nice to have: experience with cloud technologies
Strong troubleshooting and problem-solving skills
Very good English skills, both written and spoken

Stable employment and opportunity to work in a company with family traditions focused on employee growth that values personal well-being and work-life balance
Private medical care, sport package, dental care, and other social benefits.
Access to technical training