Research Engineer

Artificial Societies (societies.ai ) helps Fortune 500 organisations understand how real-world audiences think, feel, and respond — without the cost, delay, or limitations of traditional research. We build large-scale simulated populations grounded in real-world data, enabling clients to test messages, strategies, and concepts. Our clients love the ability to receive insights backed by millions of responses in hours rather than months, and to access previously inaccessible audiences (e.g. investors, CEOs, opinion leaders).

We're backed by Y Combinator
, Point
72 Ventures
, and Kindred Capital
, plus investors from Deep Mind and Sequoia Scout
, and work with leading organisations across technology, financial services, communications, and public affairs.

We're a lean and highly effective team. We move fast, hold a high bar, and trust each other to own outcomes end-to-end. The culture is collaborative but low-ego: ideas win on merit, not seniority.

We're looking for Research Engineers to work on our core simulation engine — the system that builds AI digital twin personas, assembles them into societies, and simulates their attitudes and opinions across situations.

This is not a pure research role, and it's not a pure engineering role. We need people who can move fluidly between designing rigorous evaluations, training and fine-tuning models on cloud compute, prototyping novel architectures, and shipping production code. You'll own the full research-to-production lifecycle: from formulating a hypothesis about how to better capture human nuance in a language model persona, through to deploying and monitoring the system that makes it real.

Our simulation engine poses hard problems. How do you construct an AI persona that coherently captures the beliefs, contradictions, and reasoning patterns of a real human? How do you compose thousands of such personas into a society that reflects real-world diversity and group dynamics? How do you simulate opinion distributions using language models in a way that’s statistically faithful and practically useful?

How do you design reward functions that steer model behaviour toward human-faithful outputs rather than superficially plausible ones? These are the questions you’ll work on every day.

We maintain a tight research-to-product pipeline. Our simulations power real high-stakes decisions for enterprise clients — the research has to be rigorous, and it has to ship. We’re looking for people who find it gratifying to see their work pushed to its absolute limits.

• Build and evaluate our simulation engine — design, implement, and improve the systems that construct AI personas from real-world behavioural data. You’ll work on how personas reason, how they express opinions, and how they respond to stimuli in ways that are faithful to their real-world counterparts.
• Train and fine-tune foundational models — work with the latest GPUs to train, fine-tune, and adapt language models for persona simulation. This includes designing reward functions and training objectives that steer model outputs toward human-faithful behaviour rather than generic or superficially plausible responses.
• Architect societies — develop the methods by which individual personas are composed into populations that capture meaningful human diversity, group dynamics, and emergent collective behaviour. This includes how opinion distributions arise, how sub-groups interact, and how aggregate signals remain statistically grounded.
• Write the right evals — design and build evaluation frameworks that go beyond standard benchmarks. You’ll develop rigorous statistical methods to prove the fidelity of our simulations — measuring how well our synthetic populations mirror real-world opinion distributions, demographic patterns, and response dynamics.
• Advance the state of the art — stay at the frontier of relevant research across deep learning, language model alignment, synthetic data, and computational social science. Reproduce, critique, and improve upon academic work. Translate theoretical breakthroughs into production-ready improvements.
• Ship production code — this is not a notebook-only role. You’ll write…