Six internships, one AI label, and a better way to apply

Six postings across six cities, and exactly one title contains AI. That ratio is the useful part of this list.
Open each req on the company's own careers page, check the posting date and the degree line, then decide whether the work is AI-adjacent enough to justify the application. The list gives you locations and titles only, so everything past that is verification, not assumption.
The page carries an Oct 20 date and labels the roles Summer 2026. Neither tells you whether a specific req is still accepting applications.

What the six entries actually are

• Williamsport, PA: Industrial Software Engineer Intern at Textron
• Burbank, CA: Gameplay Programmer Intern at Insomniac Games
• Palo Alto, CA: AI Core PhD Research Intern at Nubank
• NYC: Software Engineer Intern at Braze
• Fort Wayne, IN: Test Engineer Intern at Carrier Global
• Roseville, CA: ASIC Intern at Hewlett Packard Enterprise

One internship per city. That is the detail that changes how you use the page: there is no backup req in any of these locations, so one filled or closed posting takes the entire city off your board. A city list with one entry each is an index, not a shortlist.

Why the only AI-labeled role may not be your first application

"PhD" sits in the Nubank title. If you are an undergraduate, that is an eligibility mismatch on the first line, not a reach. Read the degree requirement before you spend an hour tailoring a resume. The other five titles are where most people's AI job search has to start, because they describe the systems AI work sits on: industrial software, game simulation, backend services, test infrastructure, and chips.

How to tell whether a title is AI-adjacent

The source gives no stacks, team names, or deadlines, so use the req text as the evidence and nothing else. If the Textron posting mentions controls data or instrumentation, that is closer to applied data work than the title suggests. If the Insomniac req lists C++ and performance profiling, simulation experience transfers to training environments. If the Braze posting names Python and data pipelines, that is backend work with a clear path toward ML infrastructure. Test engineering of the kind the Carrier title points at usually means building repeatable checks and reading failure output, which is the same habit model evaluation needs. An ASIC internship is hardware, though accelerator work normally needs software bring-up too.
Each of those is a conditional. Do not rewrite your resume around a guess; open the posting and look for the language and the team.

The step that fails

The common failure is applying from the location list without opening the company's own req. A directory entry can outlive the posting, and the title alone will not tell you whether the intern works on shipping code or side projects.

1. Open each company careers page. Record the req ID, the posted date, and whether the location is on-site, hybrid, or flexible.
2. Write two lines per role: the language or tool the req names, and one deliverable an intern owns.
3. Choose two applications for this week. One can be AI-labeled or AI-adjacent; the other should be a backup in a city you would actually move to.
4. Rewrite two resume bullets with the closest true evidence you have, such as a course project, a repo, or a prior internship. Do not relabel QA work as ML work.
5. Log the application date and req ID. If the company states a response window, wait it out before following up.

When the city is the only match

A single req per city makes relocation a bet on one team. Ask the recruiter whether the internship includes relocation or housing support before you price out a move, and search that company's careers page for other roles in the same city. If the req is closed, the city entry is dead; do not email the company about a posting that no longer exists.
The list is small enough to verify in an afternoon. Do that before you write a single cover letter, and the six entries become six decisions instead of six tabs you never opened.