Description

You own the operational lifecycle of enterprise AI platforms and services.

Responsibilities

• Implement and support enterprise-level AI platforms to drive IT operation excellence and onboard new use cases.
• Lead the operationalization and deployment of AI/ML models into production, ensuring high availability and performance.
• Design and develop Python solutions for automating the AI/ML model lifecycle, including data ingestion and prediction workflows.
• Implement and maintain MLOps practices for model version control, monitoring, and debugging in production.
• Build and maintain robust APIs for model serving and integration with consumer applications.

Required Skills

• 8-10 years of experience in software development focused on AI/ML operations, cloud infrastructure, and DevOps.
• Advanced proficiency in Python, including libraries such as TensorFlow, PyTorch, SciKit-learn, and Pandas.
• In-depth understanding of MLOps, covering model versioning, monitoring, deployment, and workflow automation.
• Hands-on experience with Azure Cloud services (Azure ML, Azure DevOps, Azure Functions) and Infrastructure as Code (IaC).
• Proficiency in setting up CI/CD pipelines for AI/ML models using tools like Azure DevOps or Jenkins.
• Strong experience designing and maintaining RESTful APIs for AI/ML model deployment.
• Familiarity with Large Language Models (LLMs) and transformer-based models (e.g., GPT, BERT).
• Expertise with Git and version control practices for AI system development.

Key Skills

Education

Any Graduate