Member of Technical Staff (AI for Science)

At Inherent, we are on a mission to build AI that recursively self‑improves to discover new knowledge. Scientific advances are the backbone of our economic, technological and societal prosperity, but ideas are getting harder to find and breakthroughs are becoming more expensive. We are building a new frontier lab dedicated to developing AI that explores “unknown unknowns” to uncover paradigm‑shifting research contributions. Science is a social endeavour, and so our mission is inextricably a human‑machine teaming problem. We’re starting by reinventing the AI research factory so that our own agents accelerate their own creation. Inherent is a well‑funded, fast‑growing neo‑lab backed by Tier 1 VCs who believe in our ethical stance. We are a team of operators with backgrounds at frontier labs who have done foundational work in recursive self‑improvement, AI Scientists, world modelling, meta‑RL and human‑machine cooperation. Working in‑person every day at our high‑intensity London headquarters, we believe that Europe will lead the way in the coming paradigm of AI‑enabled science, unlocking human potential across the globe.

About the role

We’re looking for Members of Technical Staff to develop transformative AI Scientist agents that make meaningful contributions to in silico and in situ discoveries in specific scientific domains. Your work will leverage our state‑of‑the‑art proprietary foundation models, adapting their capabilities to a particular scientific vertical. You will be involved in every level of the AI for Science lifecycle: judiciously selecting research problems, creating evaluations and training data, post‑training and harnessing Inherent’s models, building interfaces to infrastructure for scientific experiments (e.g., scientific software, simulators, cloud labs), driving experimental iteration on agent behaviour, and collaborating with external scientists to validate and deploy our systems. You will work closely with an experienced technical team of humans, and increasingly alongside the AI scientist collaborators we dogfood.

What you'd do

• Devise and hone AI for Science research settings in your area of expertise that are amenable to open‑ended exploration by AI Scientist agents (either in silico or in situ).
• Benchmark Inherent’s proprietary agents in your AI for Science environments, gathering data to improve agent performance via post‑training and harness iteration.
• Contribute data, evaluations, feedback and expert opinion to Inherent’s post‑training team, in service of improving our core foundation models.
• Close recursive loops wherever possible, for example by enabling our agents to automatically deploy, debug and repair themselves.
• Work closely with scientific partners and customers, which may include forward deployment.

What we're looking for

• 5+ years of experience in hard science research, AI for science, data science or industry R&D.
• Experience applying ML to drive scientific progress in silico or in situ on in‑lab or real‑world datasets.
• Demonstrated track record of success in research, whether papers, product releases, open‑source contributions, or other artifacts.
• 3+ years of software engineering experience, including familiarity with Python and at least one deep learning framework.
• Experience using the latest coding agents, and opinions about optimal workflow.
• Enthusiasm for experimental organizational design.
• AI‑pilled: adopting agents, keen to build a company where agents are front and centre.

Strong candidates may also have

• PhD in a scientific discipline.
• Contribution to a well‑cited work in AI for Science writ large (e.g., ML to predict protein structure, neural weather forecasting systems, reinforcement learning for materials discovery, or causal models for financial risk prediction).
• Hands‑on experience using AI agents to automate parts of the scientific workflow in a particular scientific vertical.
• Familiarity with post‑training and harnessing foundation models.
• An interest in AI Scientist agents, open‑endedness, meta‑learning, or recursive self‑improvement.
• Strong relationships with leading scientists in a field of scientific research amenable to low‑latency and high‑throughput experiments.
• Experience building or operating autonomous labs.

Why this is interesting

You’ll shape the core research of a frontier AI lab from the beginning. You’ll work on genuine scientific discovery — training AI scientists that empower humans to flourish — not incremental benchmark‑chasing. Small team, high trust, no bureaucracy, and a genuinely technical culture. Our products will be used by the world’s best scientists to power breakthrough research of huge benefit to humanity, while preserving human agency.

Culture

We only select people with low ego, spiky skill profiles, commitment to societal benefit, unusual viewpoints, and a passion for “living in the experiment”. We’re committed to having the most tasteful, and the weirdest, office of any AI lab: the environment shapes the agents within it.