AI internships: how the 174 listings look and when to apply

Internships are 174 of the 50,447 live listings on TixelJobs, well under 1%. For comparison, there are 1,933 entry-level roles, 223 contract roles and 113 part-time roles. The internship pool is small, and it is seasonal: it swells before the main hiring cycles and thins between them. That is why timing matters more for internships than for any other kind of role.

The listings are concentrated in the same categories as the rest of the board. ML engineering, research and data engineering internships dominate, with NLP and computer vision internships appearing mostly at research labs and larger product companies.

Internship listings are shorter than full-time ones, and the requirements are fewer but stricter:

• Current enrollment. Most listings require you to be enrolled in a degree program during the internship and often to be returning to it afterward. Read this line first; it is the most common reason an application is rejected outright.
• A field of study. Computer science, statistics, mathematics, electrical engineering or a related field. Research internships often specify a PhD program.
• Coursework or project evidence in machine learning, plus Python and one framework. The bar is lower than for full-time roles but it is not zero.
• Dates. Summer internships state a start month and a length, usually 10 to 16 weeks. Off-cycle internships are more flexible and less advertised.
• Work authorization. Internships in the United States often specify whether the company will handle visa paperwork for international students; check before you apply.

The general pattern is that large companies open summer internship applications in late summer and fall of the previous year and fill them over the winter. Research labs follow a similar calendar with earlier deadlines. Smaller companies and startups post closer to the start date, often in spring, because they plan on a shorter horizon.

The practical consequence is two search seasons. From August to November, watch the large company boards and apply as soon as a listing opens; some close once they have enough applicants rather than on a stated date. From January to April, watch the smaller companies, where the competition is thinner and the work is often broader. Off-cycle internships for fall and spring exist in smaller numbers year round and are worth a saved search on their own.

With this few listings, applying to all of them is feasible and a bad idea. Apply to the ones where you meet the enrollment and date requirements and where the work matches something you have done. A tailored application to fifteen internships beats a generic one to all 174.

• Lead with one project. A repository with a README, a result and a clear problem statement does more than a list of courses.
• Name a professor or a paper if the internship is research-flavored. It shows you read the team's work.
• Keep the resume to one page and put the enrollment status and graduation date near the top so the screener finds them.
• Follow up once, two weeks after applying, if the listing gives a contact. Internship recruiters handle large volumes and a polite nudge is normal.
• Apply to adjacent internships: data engineering, analytics and software engineering on an ML team all lead into the field.

The AI internships hub on TixelJobs collects every listing marked as an internship, and it is the page to check daily during the two seasons above. Combine it with a country page if you can only work in one place, since internships are rarely remote across borders. If you are looking for something that is internship-shaped but not labeled one, search the entry-level AI jobs hub for terms like "new grad", "early career" and "co-op", and check the contract and part-time listings, where short-term project work sometimes appears.

TixelJobs reads listings from more than 1,000 company career pages twice a day, so an internship that opens on a Greenhouse or Ashby board is picked up on the next read and reviewed before it goes live. During the fall season that is the main advantage; the large-company internship listings that close early are the ones you most need to see first.

Start at the AI internships hub on TixelJobs, then the entry-level AI jobs hub for roles a few months past graduation. The ML engineer jobs hub and the research scientist jobs hub show what the full-time versions ask for, which is useful for deciding what to build this year. The remote AI jobs page has a small number of remote internships, and the full search lets you combine internship with a country and a specialty. Browsing is free. Membership is $9 a year or $4.90 every three months and unlocks the apply link and the full description on every job. Cancel any time from your billing page.