Artificial Intelligence Engineering Intern - Summer 2027

United States·Highland Heightsentry

OtherArtificial Intelligence

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Quick Summary

Key Responsibilities

Collaborate with team members to understand business

Technical Tools

OtherArtificial Intelligence

The Artificial Intelligence Engineering Intern is responsible for supporting the development, implementation, and management of AI solutions and machine learning models that address complex business challenges. This internship position is designed to provide hands-on experience in AI development while fostering collaboration across multiple departments to create innovative solutions that enhance decision-making and business performance.

Responsibilities

~1 min read

→Collaborate with team members to understand business requirements and assist in designing scalable AI applications aligned with organizational objectives.
→Develop high-performing, reusable, and reliable code following industry standards and best practices under the guidance of senior engineers.
→Support various phases of the Software Development Life Cycle (SDLC), including requirement gathering, design, implementation, testing, deployment, documentation, and maintenance.
→Assist in building pipelines leveraging tools such as Python, Spark, Azure ML, and OpenAI.
→Work with data analysts, data engineers, and software engineers to translate business requirements into technical solutions.
→Troubleshoot, analyze, and resolve AI performance issues and production problems.
→Maintain up-to-date knowledge of advancements in AI, machine learning, and data engineering.
→Participate actively in team meetings, contributing ideas and insights to drive continuous improvement.
→Create necessary documentation relating to work produced during the internship.

Requirements

~1 min read

Currently pursuing a Bachelor's degree or higher in Computer Science, AI, Data Science, or a related field.
Strong foundational knowledge of Python programming (e.g., Spark, pandas) and SQL.
Familiarity with AI methodologies, including supervised/unsupervised learning, regression analysis, and neural networks.
Practical knowledge of cloud platforms, particularly Azure (Azure Synapse, Azure ML, Azure Data Factory, Azure Functions).
Exposure to software development fundamentals such as SOLID principles, Object-Oriented Design, and Domain Driven Design.
Strong problem-solving skills and a proactive attitude.