AI Engineering Intern

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At Light, 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 Light. 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.
Who this is for
You must meet both of these requirements:
Currently studying at University of Oxford, or University of Cambridge.

A silver medal or higher at the International Mathematical Olympiad (IMO) or International Olympiad in Informatics (IOI), or an equivalent level of achievement in another highly competitive endeavour.

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 Light 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.
What you’ll work on
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.
Help agents learn from their work. Our agent reviews merged pull requests and corrections to update its repository-specific instructions. You’ll shape that process, catch misleading lessons, and test whether new instructions improve its performance.

Train and deploy LLM and ML models. Fine-tune SoA LLM models. Run experiments, compare results against the existing pipeline, and establish whether a model is ready for production. Leverage ML tools to enhance the ability of our Agents via e.g. K-means, t-sne, PCA, random forest trees etc. etc.

Build Agents. Take full end to end ownership of an agent. Agent do pre-emptive support for the self-healing pipeline; they fix; they communicate with customers; etc.

Build evaluations and review tools. Define what a correct answer looks like, create tests that expose failures, and help catch poor output before it reaches customers.

Own projects through delivery. Scope the problem, build the solution, debug regressions, and follow through until the customer can rely on what you’ve shipped.

You’ll work alongside exceptional colleagues.
What else we’re looking for
Strong programming ability.

Something you’ve built beyond coursework or tutorials: a model, agent, tool, or application that does useful work.

Hands-on experience with AI tooling, such as LLM APIs, agent frameworks, model fine-tuning, or automated workflows.

A habit of investigating why a system failed and testing whether your fix addresses the cause.

Clear thinking and the ability to explain your decisions, including what you tried and why it didn’t work.

Open-source contributions, deployed models, and experience building evaluation pipelines are a plus.
How we’ll measure success
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.
What you’ll get
Internship compensation above the standard market rate.

A role based in our London office, working alongside the product and engineering team.

Ownership from your first day, with a path to shipping work into production.

How to apply
Send your CV.
Include a link to something you’ve shipped. Tell us what it does, which parts you built yourself, where it failed, and how you fixed it. Then explain why you want to work on organic software at Light.
We want to understand how you think, what you can build, and what you’re ready to take on next.
Light is an equal opportunity employer.
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在Light，我们正在重新定义软件如何构建、如何交付以及如何运作。
我们正在构建有机软件。能够自我修复的软件。能够适应用户和业务的软件。能够在使用中学习和不断改进的软件。
我们的起点是金融。包括Legora、Lovable和Fuse Energy在内的公司已经在Light上运行。我们正在构建一个理解每个企业如何运作并与之共同演进的平台。
作为AI工程实习生，你将帮助实现这一目标：构建能够识别错误、改进自身行为并证明这些改进有效的系统。你将参与智能体、模型和基础设施的工作，使有机软件成为客户可以信赖的东西。
适合谁
你必须同时满足以下两项要求：
目前在University of Oxford或University of Cambridge就读。

在国际数学奥林匹克（IMO）或国际信息学奥林匹克（IOI）中获得银牌或更高奖项，或在其他高度竞争性领域取得同等水平的成就。

如果你以同等成就申请，请说明竞赛或领域、你的成绩以及达到该成绩所需的标准。如果你在Oxford/Cambridge就读但没有同等水平的成就，我们建议你不要申请。
我们对Light实习生的标准很高。你需要有探索陌生领域的好奇心、为把事情做对而付出额外努力的意愿、检验假设的纪律性，以及当第一种方法行不通时坚持下去的毅力。
你将参与的工作
你将可以使用我们的代码仓库、真实的工程问题，以及一个已经能对生产代码发起拉取请求的内部编码智能体。你的工作将帮助这些系统变得更有能力和更可靠。
帮助智能体从工作中学习。我们的智能体会审查已合并的拉取请求和修正内容，以更新其针对特定仓库的指令。你将塑造这一过程，发现误导性的经验教训，并测试新指令是否提升其表现。

训练和部署LLM和ML模型。微调SoA LLM模型。运行实验，将结果与现有流水线进行比较，并确定模型是否已准备好投入生产。利用ML工具增强我们智能体的能力，例如K-means、t-sne、PCA、随机森林树等。

构建智能体。对一个智能体承担完整的端到端责任。智能体为自愈流水线提供先发支持；它们进行修复；它们与客户沟通；等等。

构建评估和审查工具。定义正确答案的样子，创建能暴露失败的测试，并帮助在不良输出到达客户之前将其捕获。

主导项目直至交付。界定问题范围，构建解决方案，调试回归问题，并持续跟进，直到客户能够信赖你所交付的东西。

你将与杰出的同事一起工作。
我们还希望看到
较强的编程能力。

你在课程作业或教程之外构建过的东西：一个能完成有用工作的模型、智能体、工具或应用。

使用AI工具的实践经验，例如LLM API、智能体框架、模型微调或自动化工作流。

追查系统失败原因并测试你的修复是否解决根本原因的习惯。

清晰的思维以及解释你决策的能力，包括你尝试了什么以及为什么没有成功。

开源贡献、已部署的模型以及构建评估流水线的经验是加分项。
我们将如何衡量成功
你的工作应产生可衡量的改进：智能体生成的更改更正确、模型准确率更高、到达用户的失败更少，或团队持续使用的工具。你将帮助定义这些衡量标准，并用它们来评估你所构建的东西。
你将获得
高于市场标准的实习薪酬。

一个位于我们London办公室的职位，与产品和工程团队一起工作。

从第一天起就拥有主导权，并有将工作交付到生产的路径。
如何申请
发送你的简历。
包含一个你已交付作品的链接。告诉我们它做什么、哪些部分是你自己构建的、它在何处失败，以及你如何修复它。然后解释你为什么想在Light从事有机软件的工作。
我们想了解你如何思考、你能构建什么，以及你准备好接下来承担什么。
Light是一个机会均等的雇主。
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