1. PURPOSE AND SCOPE

The AI Engineer Intern supports AI/ML model development, particularly in Generative AI, by assisting in research, implementation, and deployment. Interns will work on MLOps pipelines, AI model optimization, and cloud integration using tools like Docker, Kubernetes, and Git. They will collaborate with cross-functional teams to analyze data, monitor AI models, and improve efficiency. This role provides hands-on experience in AI technologies and real-world problem-solving.

2. RESPONSIBILITY

Responsibilities include, but are not limited to:

• Research and develop AI/ML models, particularly in Generative AI.
• Implement, test, and optimize AI models for real-world applications.
• Assist in building and maintaining MLOps pipelines to streamline model deployment.
• Collaborate with cross-functional teams to analyze data and improve model performance.
• Integrate AI solutions with cloud platforms and containerization tools like Docker, Kubernetes.
• Debug and troubleshoot AI models, ensuring high accuracy and efficiency.

3. QUALIFICATIONS AND KNOWLEDGE

• Pursuing or recently completed a degree in Computer Science, AI, or related field.
• Strong knowledge of Machine Learning, Deep Learning, and AI frameworks.
• GPA: 3.2/4.0 or higher (preferred for strong academic performers).
• Experience with Python and data preprocessing.
• Familiar with MLOps, cloud platforms, and containerization (Docker, Kubernetes) is a plus.
• Excellent problem-solving, teamwork, and communication skills.