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

Technical 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)

Preferred skills

Technology->AI-AI Engineering->MLOps,Technology->AI-Data science->PYTHON - AI-Data Science

Education

MCA,MSc,MTech,BTech