Task & Job Responsibilities-

· Design, develop, and maintain scalable infrastructure and platform components for ML and LLM    solutions.

· Utilize containerization technologies (Docker/Podman) and orchestration tools (Kubernetes) to deploy and manage data and ML applications.

· Implement, manage and monitor scalable data, CI/CD and MLOps pipelines.

· Manage the entire lifecycle of ML and LLM models, from data preparation and model training to deployment and monitoring.

· Collaborate with data scientists, ML architects, software engineers, and other stakeholders to understand data and model requirements and deliver solutions.

· Apply best practices in MLOps and LLMOps to streamline model development, deployment, and management.

· Stay updated with the latest trends and advancements in data engineering, MLOps, and LLMOps.

· Up-to-date knowledge in Microsoft technologies (MS-Fabric, Data Lake etc..)

Profile-

· New AI projects need to be staffed by an experienced engineer (10+ years’ experience in software or data engineering, +3 years’ experience in MLOps/AIOps engineering).

· Service ownership of LakeFS and some more technologies around DevOps platform.

· Needs to work on long term vision with MS technologies together (MS Fabric with power BI, AI and building concept with modern data lake.