Research Engineer

Founding RL Engineer/Researcher (Juniors welcome also)

Remote | London / Paris preference but EU based a must | £300,000 + founding Equity

The best AI engineers aren't waiting for a job ad. They're waiting for the right moment. This might be it.

Anthropic leadership has discussed spending over $1 billion on RL environments in the next year alone. The market is moving - fast and at scale. One pre‑seed company just closed a round at a valuation most Series A companies would envy, with frontier AI labs already as paying clients and acquisition interest already on the table (x2).

The reason? They cracked something the rest of the market hasn't.

Most teams build RL environments from synthetic data - easy to demo, easy to commoditise, brittle. This team mines real human behavioural data - how domain experts actually reason, decide, and solve complex tasks over long‑horizon workflows: 10–100+ step environments. Closed‑loop systems where environments, data, training, and evaluation are tightly integrated. Not proxies. Not short cuts.

25–30% uplift in model task success rates. 50–65% more training signals. Evals that reflect how humans actually work.

The funding just landed. Second time founders. The founding team is being built right now. There are very few seats. Are you going to be in one of them?

• £300,000 + founding equity at a ~$30M pre‑seed valuation
• Frontier AI labs as paying clients from day one
• Environment design treated as a first‑class problem - not an after thought
• London / Paris hybrid with remote options
• Get in now – before this role disappears and you're watching from the outside

You’ll love this if…

• You’ve built RL environments, gyms, or training infrastructure at a serious RL or AI company
• You think environment design & the lack of data available are the most underrated problems in AI right now
• You move fast, think in first principles, and thrive without a playbook
• You want to work at the forefront of innovation with frontier labs

You can apply today. Because great teams are built differently.