Job Title: MLOps Engineer Location: 100 percent remote ( USA ) - EST Duration: 4 month contract ( potential for extension ) Visa : / L2/ / GC Need 12+ Years of experience

Skillset : Kubernetes, AKS, Azure cloud, Azure DevOps, Databricks Nice to have : MLOps, ML Infrastructure deployments

We are seeking for an experienced ( ML ) Machine Learning Operations Engineer and experience working with design, development & implementation of AI / ML applications & managing the lifecycle of Machine Learning models.

The role is MLOps Engineer, intersection of Data Scientist, Data Engineer, & DevOps Engineer. You will be working in a team of engineers that takes on a wide array of responsibilities that encompass building all the infrastructure necessary to take a trained ML Model , integrate & deploy, making it available to other applications.

RESPONSIBILITIES

Design & deploy scalable infrastructure for ML workloads using cloud platforms & containerization technologies ( e.g., Docker, Kubernetes )

Need to Work with teams, to design & build cloud hosted, automated pipelines that run, monitor, & retrain ML Models for business applications

Design & implement Model & Pipeline validation procedures alongside teams of Data Scientists, Data Engineers, & other ML Engineers

Optimize & refactor development code so that it can be moved to production

Need to Build Data, Feature Engineering Pipelines for new & existing models

Assemble configurations & specifications to automatically build environments in production

Create & develop in CI / CD Pipelines which allow for controlled & continuous enhancement of existing work & new features during both development & production phases