At a Glance
- Tasks: Build cutting-edge RL infrastructure and design long-horizon environments using real human data.
- Company: Join a pioneering AI startup with significant funding and ambitious goals.
- Benefits: Competitive salary of £220,000 plus equity in a high-potential pre-seed company.
- Other info: Limited positions available; apply now to secure your spot in this dynamic team.
- Why this job: Be part of a revolutionary team shaping the future of AI with real impact.
- Qualifications: Experience in building RL environments and a passion for innovative AI solutions.
Remote | London / Paris preference but EU based a must | £220,000 + 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 shortcuts.
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?
£220,000 + 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 afterthought. London / Paris a preference but remote in Europe a must. Get in now - before this role disappears and you're watching from the outside.
What you'll be doing:
- Building closed-loop RL infrastructure - environment harness, verifiers, reward models, gym infrastructure
- Designing and extending long-horizon RL environments grounded in real expert behavioural data
- Turning raw human workflows into clean, production-ready training signals
- Running training experiments to prove the gyms produce real capability gains
- Making architecture decisions that will define the platform for years - alongside second time founders who've built and shipped at scale
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 is the most underrated problem in AI right now
- Long-horizon RL excites you more than short-form RLHF
- You move fast, think in first principles, and thrive without a playbook
- Python and PyTorch are second nature - and you know what makes a great training environment, not just a functional one
Roles like this don't stay open. If it fits - move. Because great teams are Built Different.
Founding RL Engineer in London employer: Built Different Talent
Join a pioneering team at the forefront of AI innovation, where your contributions as a Founding RL Engineer will directly shape the future of reinforcement learning. With a competitive salary of £220,000 plus equity, you'll thrive in a dynamic remote work culture that values creativity and expertise, while collaborating with seasoned founders and industry leaders. This is an exceptional opportunity to grow alongside a company poised for rapid success, leveraging real human behavioural data to redefine AI training environments.
StudySmarter Expert Advice🤫
We think this is how you could land Founding RL Engineer in London
✨Tip Number 1
Network like a pro! Reach out to people in the AI and RL space, especially those who might be connected to the company you're eyeing. A friendly chat can open doors that applications alone can't.
✨Tip Number 2
Show off your skills! If you’ve got a portfolio or any projects related to RL environments, make sure to highlight them. Share your work on platforms like GitHub or even create a personal website to showcase what you can do.
✨Tip Number 3
Prepare for the interview like it’s the championship game. Research the company’s recent projects and challenges in RL. Be ready to discuss how your experience aligns with their goals and how you can contribute to their success.
✨Tip Number 4
Don’t just apply – engage! When you find a role that excites you, apply through our website and follow up with a message expressing your enthusiasm. It shows initiative and can help you stand out from the crowd.
We think you need these skills to ace Founding RL Engineer in London
Some tips for your application 🫡
Show Your Passion for RL:When you're writing your application, let your enthusiasm for reinforcement learning shine through. We want to see that you’re not just ticking boxes but genuinely excited about building closed-loop systems and tackling long-horizon challenges.
Tailor Your Experience:Make sure to highlight your relevant experience in building RL environments or training infrastructure. We love seeing specific examples of how you've tackled complex tasks and what impact your work had on previous projects.
Be Clear and Concise:While we appreciate detail, clarity is key! Keep your application straightforward and to the point. Use bullet points if it helps convey your skills and experiences more effectively.
Apply Through Our Website:Don’t forget to submit your application through our website! It’s the best way for us to keep track of your application and ensure it gets the attention it deserves. Plus, it shows you’re serious about joining our team!
How to prepare for a job interview at Built Different Talent
✨Know Your RL Stuff
Make sure you brush up on your reinforcement learning concepts, especially around closed-loop systems and long-horizon environments. Be ready to discuss your past experiences in building RL infrastructure and how you've tackled challenges in this area.
✨Showcase Your Problem-Solving Skills
Prepare to demonstrate your ability to think in first principles. Think of examples where you've had to design or improve RL environments, and be ready to explain your thought process and the impact of your decisions.
✨Familiarise Yourself with Their Approach
Research the company’s unique approach to mining real human behavioural data. Be prepared to discuss how this differs from traditional methods and why you believe it’s a game-changer in the RL space.
✨Ask Insightful Questions
Prepare thoughtful questions that show your genuine interest in the role and the company. Inquire about their vision for the future of RL environments and how they plan to leverage their funding to innovate further.
