Description

You will operationalize data science projects and manage the full lifecycle of AI models in production environments.

Responsibilities

• Own the lifecycle management of production AI models, including continuous deployment, retraining, and troubleshooting.
• Design and build automated cloud-based pipelines to run, monitor, and retrain ML models using agile methodologies.
• Implement scalable solutions for model governance, behavior analytics, and drift monitoring.
• Develop CI/CD pipelines to support continuous enhancement of existing features and new model releases.
• Collaborate with data scientists to translate AI models into production-ready solutions aligned with business KPIs.

Required Skills

• 10+ years of professional experience in technical roles.
• Proficiency in Python and PySpark.
• Hands-on experience with MLFlow and Azure Databricks.
• Experience with Azure Data Lake Storage (ADLS) and Snowflake.
• Strong knowledge of Azure DevOps for CI/CD pipeline development.
• Experience managing workloads in Kubernetes and microservices architectures.
• Competency with API development and integration.
• Working knowledge of various database technologies including SQL, NoSQL, Blob, and object storage.
• Experience with messaging platforms such as Kafka, Azure EventHub, or IoT Hub.

Preferred Skills

• Experience in cloud analytics service discovery, design, and migration within Azure.
• Background in agile product development and cross-functional team collaboration.

Key Skills

Education

Any Graduate