2025-AI-College-Jobs: Daily Updated AI/ML Internships and New Grad Listings

Project Overview

Introduction

The ‘2025-AI-College-Jobs’ project is a valuable resource for college students seeking internships or new graduate positions in the fields of Artificial Intelligence (AI), Machine Learning (ML), and Data Science. This repository provides a daily updated list of available jobs, focusing on positions posted within the last 120 days. It includes a comprehensive breakdown of internships and new graduate opportunities in both the USA and internationally, covering top companies such as FAANG and quant firms. This project is worth exploring as it simplifies the job search process, saving time and effort for students looking to kickstart their careers in AI and related fields.

Key Features

The “2025-AI-College-Jobs” project is a comprehensive repository listing AI, ML, and Data Science job opportunities for college students seeking internships or new graduate positions. The repository is updated daily and prioritizes jobs posted within the last 120 days. It includes listings from various categories such as FAANG companies, quantitative research firms, and other industries. The project provides detailed information on job positions, locations, salaries, and posting ages, making it a valuable resource for students to find relevant and timely job opportunities in the AI and Data Science fields.

Real-World Applications

The “2025-AI-College-Jobs” repository is a valuable resource for college students seeking internships or new graduate positions in Artificial Intelligence (AI), Machine Learning (ML), and Data Science. Here are some practical ways users can benefit from this repository:

• Users can browse through the extensive list of internships and new graduate positions in the USA and internationally, categorized by companies such as FAANG+, Quant firms, and other industries.
• Each listing includes details like company, position, location, salary, and the age of the posting, helping users find recent and relevant opportunities.

Filtering by Location and Type

• Students can filter jobs based on their preferred location, whether in the USA or internationally, to find opportunities that align with their geographical preferences.
• They can also focus on specific types of roles, such as research scientist internships, machine learning engineer positions, or quantitative analyst roles.

Salary and Company Information

• The repository provides salary information for many listings, allowing students to compare compensation packages and make informed decisions.
• Detailed company information helps students understand the work environment and requirements of each role.

Additional Resources

• The repository mentions other useful resources like the “SpeedyApply: Job Application Autofill Tool” Chrome extension, which can help streamline the job application process.
• It also directs users to other related job lists, such as software engineering positions, for those with broader interests.

Staying Updated

• Since the positions are updated daily and prioritize jobs posted within the last 120 days, users can ensure they are looking at current and relevant job opportunities.

By leveraging this repository, college students can efficiently search for and apply to AI, ML, and Data Science jobs that match their skills and career goals.

Conclusion

The “2025-AI-College-Jobs” project has a significant impact on college students and new graduates seeking internships or full-time positions in AI, ML, and Data Science. Here are the key points:

• Comprehensive Job List: The repository provides a daily updated list of over 700 internship and new graduate positions across the USA and internationally, focusing on FAANG companies, quantitative firms, and other industries.
• Job Categories: Jobs are categorized into FAANG+, Quantitative Research, and Other industries, making it easier for students to find relevant opportunities.
• Salary Information: Many listings include salary details, helping students make informed decisions.
• Geographical Diversity: Positions are available in various locations worldwide, offering a broad range of options for students.
• Future Potential: This resource can help bridge the gap between academia and industry by providing direct access to job opportunities, potentially increasing the number of skilled professionals in AI and related fields.

Overall, the project enhances job search efficiency and career prospects for students in the AI and Data Science sectors.

For further insights and to explore the project further, check out the original speedyapply/2025-AI-College-Jobs repository.

Attributions

Content derived from the speedyapply/2025-AI-College-Jobs repository on GitHub. Original materials are licensed under their respective terms.