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United States Digital Space LLC in London is offering an AI Engineering Intern role. You will work on systems that identify mistakes, improve behaviour, and prove improvements.
You’ll work on agents, models, and infrastructure to turn organic software into reliable products. You’ll gain access to repositories, real engineering problems, and an internal coding agent that opens pull requests against production code.
At the company, we’re redefining how software is built, how it’s delivered, and how it works.
We’re building organic software. Software that heals itself. Software that adapts to the user and the business. Software that learns and gets better as it’s used.
Our starting point is finance. Companies including Legora, Lovable, and Fuse Energy already run on the company. We’re building towards a platform that understands how each business operates and evolves with it.
As an AI Engineering Intern, you’ll help make that happen: building systems that identify mistakes, improve their own behaviour, and prove those improvements work. You’ll work on the agents, models, and infrastructure that turn organic software into something customers can rely on.
You must meet both of these requirements:
If you’re applying with an equivalent achievement, explain the competition or field, your result, and the standard required to achieve it. If you’re at Oxford/Cambridge and you don’t have an equivalent level of achievement we encourage you to not apply.
Our bar for internships at the company is high. You will need the curiosity to explore unfamiliar areas, the willingness to go the extra mile to get things right, the discipline to test your assumptions, and the persistence to keep going when your first approach does not work.
You’ll have access to our repositories, real engineering problems, and an internal coding agent that already opens pull requests against production code. Your work will help make these systems more capable and reliable.
You’ll work alongside exceptional colleagues.
Open‑source contributions, deployed models, and experience building evaluation pipelines are a plus.
Your work should produce measurable improvements: more correct agent‑generated changes, better model accuracy, fewer failures reaching users, or tools the team continues to use. You’ll help define those measures and use them to assess what you build.
the company is an equal opportunity employer.