AI & Cloud Engineering Intern (Azure-Focused)

Overview

Remote
On Site
Hybrid
Depends on Experience
Contract - W2
Contract - 7 Month(s)
Able to Provide Sponsorship

Skills

AI
artificial intelligence
machine learning
azure
Microsoft Azure
Machine Learning Operations (ML Ops)

Job Details

We are seeking a motivated and technically skilled AI & Cloud Engineering Intern to join our team. This role is ideal for a graduate student pursuing a Master s in Artificial Intelligence with a strong foundation in software development, machine learning, and cloud technologies. The intern will support the design, development, and deployment of intelligent solutions using Azure AI services, big data tools, and machine learning frameworks.
Key Responsibilities:
Collaborate with senior AI engineers to design and implement machine learning models for NLP, prediction, and classification tasks.
Deploy and manage models using Azure Machine Learning, Azure Databricks, and Azure Functions.
Assist in data ingestion, preprocessing, and transformation using Big Data tools like Spark and Hadoop.
Build and visualize data pipelines using Azure Data Factory and Power BI.
Participate in the development of APIs and microservices for AI-powered applications.
Monitor and optimize AI workloads in the cloud for performance and scalability.
Document project workflows, model performance, and system architecture.
Required Skills & Qualifications:
Currently pursuing a Master s degree in Artificial Intelligence, Computer Science, or related field.
Completed coursework in Machine Learning, NLP, Big Data, Feature Engineering, Software Development for AI, and Data Visualization.
Strong programming skills in Python and familiarity with ML libraries such as Scikit-learn, TensorFlow, or PyTorch.
Understanding of Azure Cloud services (e.g., Azure ML, Azure Functions, Blob Storage, Azure DevOps).
Experience with data visualization tools like Matplotlib, Seaborn, or Power BI.
Familiarity with version control (e.g., Git) and CI/CD practices.
Preferred Qualifications:
Knowledge of MLOps, containerization (Docker), and orchestration (Kubernetes).
Exposure to SQL and NoSQL databases.
Experience working on academic or personal projects involving AI and cloud.
Program Benefits:
Mentorship from experienced AI and Cloud professionals.
Opportunity to work on real-world cloud-based AI projects.
Access to Azure credits and learning resources.
Potential for full-time conversion based on performance.

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