ML Engineer (£100k-£180k + Equity) at Artificial Societies Ltd
- London, United Kingdom
Posted yesterday
About the role
This is a job that Jill, our AI Recruiter, is recruiting for on behalf of one of our customers.
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Job Title
ML Engineer
Salary
£100k-£180k + Equity
Company Description
Artificial Societies Ltd is a YC W25 startup backed by Point72 and Kindred Capital building a Societal World Model to simulate human opinion and influence.
Job Description
You will own the transition from frontier research to production, building models that simulate thousands of individuals in real-time. By post-training and distilling language models, you’ll enable Fortune 500 organizations to test strategies against simulated populations, solving complex combinatorial problems at the absolute edge of machine learning capability and scale.
Location
London, UK
Why this role is remarkable
- Work on a "Societal World Model," tackling combinatorial challenges harder than protein folding to simulate how specific individuals influence each other across a multiverse of scenarios.
- Join an elite team backed by Y Combinator, Point72 Ventures, and Kindred Capital, featuring investors from DeepMind and Sequoia Scout who are redefining social science through ML.
- Deploy systems at massive scale; our simulations have previously utilized 2% of Google’s global AI throughput to inform strategies for clients with over $3T in market cap.
- Take novel research prototypes and turn them into production-grade simulation systems that deliver actionable insights to the world's most influential organizations.
- Post-train, fine-tune, and distil frontier language models to make large-scale simulations fast, efficient, and nuanced enough to represent real-world populations.
- Design and own the end-to-end data pipelines and inference infrastructure required to serve simulations of thousands of individuals reliably and at scale.
- Has at least 2+ years of experience shipping machine learning models into production within a fast-paced startup environment, taking ownership from notebook to user.
- Possesses deep hands-on expertise in post-training language models, including RL, distillation, and reward design, rather than just classical machine learning techniques.
- Writes high-quality, maintainable Python and maintains a strong intuition for statistics, probability, and reasoning within high-dimensional spaces to solve hard frontier problems.
Ok, I'll go first. I'm Jack, an AI that gets to know you on a quick call, learning what you're great at and what you want from your career. Then I help you land your dream job by finding unmissable opportunities as they come up, supporting you with applications, interview prep, and moral support.
And I'm Jill, an AI Recruiter who talks to companies to understand who they're looking to hire. Then I recruit from Jack's network, making an introduction when I spot an excellent candidate.
How does this work?
- Jack's an AI agent for job searching and career coaching. He works for you.
- Jill is the AI recruiter working for the company. She recruits from Jack's network.
- If it's a match and the company wants to meet you, they'll make the intro. In the meantime, if you'd like, Jack will send you excellent alternatives.
This isn't a trick. This is an open role that Jill is currently recruiting for from Jack's network.
Sometimes Jill's clients ask her to anonymize their jobs when she advertises them, which means she can't share all the details in the job description.
We appreciate this can make them look a bit suspect, but there isn't much we can do about it.
Give Jack a spin! You could land this role. If not, most people find him incredibly helpful with their job search, and we're giving his services away for free.