awesome-ml-internships

What the ML internship list provides

AI and Machine Learning Internships 2027 is a GitHub repository that collects live artificial intelligence and machine learning internships for students. The README describes the list as refreshed through the Zapply job pipeline, which means the entries are pulled from that pipeline rather than typed by hand in a single batch. The badge at the top shows about 90 companies represented, giving a sense of the breadth of employers currently tracked. The focus is specifically on AI and ML internships, which sets it apart from the broader new grad and general internship lists in the same family of repositories. Because the data is live and pipeline driven, the list is meant to reflect current openings rather than a static archive, and the company count badge is the quick signal of how many employers are in the set at the moment. The README frames the project as a resource for students looking for internship experience in machine learning and related fields, and the pipeline approach is what keeps the entries flowing without a large manual curation step. For a student targeting ML roles, the value is a focused list that does not mix in unrelated disciplines, so the scanning effort goes toward the most relevant postings. The real time nature also means the count can change as the pipeline adds or removes companies, so the badge is a live indicator rather than a fixed total.

The Zapply pipeline and community links

The README ties the list to Zapply, the same website and Chrome extension used by the sibling job lists. Zapply offers an extension that autofills job applications in seconds, a dedicated job board featuring the latest openings, user accounts with multiple profiles for different resume types and roles, and application tracking with streaks and commitment awards. The README presents these as part of an advanced career journey built around the listings. An Explore Around section links to a Discord server and a LinkedIn page where students and new grads can connect and seek advice from a growing network of peers. The Discord and LinkedIn communities are the human layer of the project, giving readers a place to discuss ML internship choices rather than only reading the list. The GitHub repository is the open data surface, while Zapply is the hosted tooling that helps turn the listings into submitted applications, and in this case the pipeline is also what feeds the list. The README describes Zapply at the feature level only, naming the extension, the board, the accounts, and the tracking, without implementation detail, so a reader knows what is available before following the linked buttons. This split keeps the list simple while the companion site handles the application workflow.

Contributing and keeping the pipeline fed

Contribution remains part of the project even though the list is pipeline driven. The README's tip invites readers to help the list grow by submitting an issue with new internships and points to a contributing guide for the steps, so a student who finds an ML role that the pipeline missed can still add it. Because the repository accepts issues and pull requests alongside the automated pipeline, the company count badge can move as both human contributions and pipeline updates land, and the last update badge shows how recent the latest activity is. This hybrid model blends automated refresh with community correction, which is why the README keeps asking for help even when much of the data is fetched automatically. The project pairs a main list with a contributing guide so a newcomer can follow a known path instead of guessing the format. The companion tools, the Zapply site and the community servers, give readers a reason to return, and that return traffic tends to surface more missing roles. The README does not print the full internship table up front; it uses the badge and the contributing pointers to convey scale and process. For a student building a target list, the benefit is that the pipeline does most of the gathering while the contributing guide explains how to fill gaps when a relevant ML internship is not yet present.

Editorial conclusion

AI and Machine Learning Internships 2027 is a live list of about 90 companies refreshed through the Zapply job pipeline and paired with the Zapply autofill extension for applications.