As an AI Engineering Intern, you will work closely with engineers and data scientists to design, build, and evaluate machine learning and AI‑driven solutions. This role offers hands‑on experience across the full AI development lifecycle—from data preparation and model experimentation to prototyping and deployment. You will contribute to real‑world projects while gaining exposure to modern AI technologies, including large language models (LLMs) and agent‑based applications where applicable.

Key Responsibilities

• Collaborate with engineers and data scientists to design and implement machine learning and AI solutions
• Develop, train, and evaluate machine learning models (e.g., classification, regression, recommendation systems, NLP)
• Assist in building AI‑powered features or prototypes, including LLM‑ or agent‑based applications when relevant
• Perform data processing, feature engineering, and model experimentation
• Write clean, well‑documented, and testable code primarily in Python (and other applicable languages as needed)
• Analyze model performance, conduct experiments, and clearly communicate results and insights
• Support the integration of AI models into backend services, APIs, or existing workflows
• Stay current with emerging AI technologies, tools, and best practices

Required Qualifications

• Currently pursuing a Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, Data Science, Engineering, or a related field
• Coursework or hands‑on experience with machine learning concepts and algorithms
• Proficiency in Python and familiarity with ML/AI libraries (e.g., PyTorch, TensorFlow, scikit‑learn, Hugging Face)
• Basic understanding of data preprocessing, model training, and evaluation techniques
• Strong problem‑solving skills and attention to detail
• Ability to communicate technical concepts clearly to both technical and non‑technical audiences

Preferred Qualifications

• Experience with deep learning, NLP, or recommendation systems
• Exposure to LLMs, prompt engineering, or agent‑based frameworks
• Familiarity with APIs, backend services, or cloud platforms
• Experience working with version control systems (e.g., Git)