Mindteck
Cloud DevOps Engineer II
REMOTE
Preferred location: nearshore (or offshore)
Skillset: Kubernetes, AKS, Azure cloud, Azure DevOps, Databricks
Nice to have: MLOps, ML Infrastructure deployments
Description:
We are looking for an experienced Machine Learning Operations Engineer who has experience working with the design, development, and implementation of AI/ML applications and managing the lifecycle of Machine Learning models. The role of an MLOps Engineer is at the intersection of Data Scientist, Data Engineer, and DevOps Engineer. You'll work in a team of engineers responsible for building infrastructure necessary to deploy trained ML Models, integrate, and make them available to other applications. Job Responsibilities:
Design and deploy scalable infrastructure for ML workloads using cloud platforms and containerization technologies (e.g., Docker, Kubernetes). Work with teams to design and build cloud-hosted, automated pipelines that run, monitor, and retrain ML Models for business applications. Design and implement Model and Pipeline validation procedures alongside Data Scientists, Data Engineers, and ML Engineers. Optimize and refactor development code for production deployment. Build Data and Feature Engineering Pipelines for models. Configure environments automatically in production. Create CI/CD Pipelines for continuous development and deployment. We care about our people and our work. We have a diverse team of over 1,000 professionals experiencing a range of challenges and opportunities. Learn more at Mindteck Careers. Mindteck is an Equal Opportunity Employer. All qualified applicants will receive consideration without regard to race, religion, color, national origin, sex, sexual orientation, gender identity, age, veteran status, disability, or any other protected trait. #J-18808-Ljbffr
We are looking for an experienced Machine Learning Operations Engineer who has experience working with the design, development, and implementation of AI/ML applications and managing the lifecycle of Machine Learning models. The role of an MLOps Engineer is at the intersection of Data Scientist, Data Engineer, and DevOps Engineer. You'll work in a team of engineers responsible for building infrastructure necessary to deploy trained ML Models, integrate, and make them available to other applications. Job Responsibilities:
Design and deploy scalable infrastructure for ML workloads using cloud platforms and containerization technologies (e.g., Docker, Kubernetes). Work with teams to design and build cloud-hosted, automated pipelines that run, monitor, and retrain ML Models for business applications. Design and implement Model and Pipeline validation procedures alongside Data Scientists, Data Engineers, and ML Engineers. Optimize and refactor development code for production deployment. Build Data and Feature Engineering Pipelines for models. Configure environments automatically in production. Create CI/CD Pipelines for continuous development and deployment. We care about our people and our work. We have a diverse team of over 1,000 professionals experiencing a range of challenges and opportunities. Learn more at Mindteck Careers. Mindteck is an Equal Opportunity Employer. All qualified applicants will receive consideration without regard to race, religion, color, national origin, sex, sexual orientation, gender identity, age, veteran status, disability, or any other protected trait. #J-18808-Ljbffr