MLOps Engineer

We are looking for an experienced MLOps Engineer to design, deploy, automate, and maintain scalable machine learning platforms and workflows. The ideal candidate should have hands-on experience with ML lifecycle management, CI/CD pipelines, cloud platforms, containerization, and model deployment.

Responsibilities

• Responsible for successful delivery of MLOps solutions and services in client consulting environments; • Define key business problems to be solved; formulate high level solution approaches and identify data to solve those problems, develop, analyze/draw conclusions and present to client. • Assist clients with operationalization metrics to track performance of ML Models • Help team with ML Pipelines from creation to execution • Guide team to debug issues with pipeline failures • Understand and take requirements on Operationalization of ML Models from Data Scientist • Engage with Business / Stakeholders with status update on progress of development and issue fix • Setup Standards related to Coding, Pipelines and Documentation • Research on new topics, services and enhancements in Cloud Technologies

Requirements

Machine Learning & MLOps ML lifecycle management Model deployment and monitoring Feature stores and model registries Experiment tracking Tools & Frameworks MLflow Kubeflow Airflow TensorFlow / PyTorch / Scikit-learn Apache Spark (preferred)