At a Glance
- Tasks: Lead the development of cutting-edge reinforcement learning agents for autonomous software testing.
- Company: Join a venture-backed AI company transforming software quality with innovative technology.
- Benefits: Equity, unlimited resources, and a collaborative environment focused on execution.
- Why this job: Make a real impact by redefining software testing in the age of AI.
- Qualifications: 5+ years in ML production, deep RL expertise, and Python/PyTorch mastery.
- Other info: Be part of a small, elite team shaping the future of technology.
The predicted salary is between 72000 - 108000 ÂŁ per year.
Change Software Forever. QA slows the world down. Flaky tests kill trust, stall releases, and bleed engineering velocity. Duku AI is ending that era. We're building autonomous agents that think like engineers: they run every critical user journey, catch failures before users do, and self-heal as the codebase evolves. Real AI teammates, not test scripts that break on impact.
We're venture-backed and led by operators who've scaled Meta's testing infrastructure, launched Uber's global playbooks, and grew Deliveroo from zero to hypergrowth. We know what elite execution looks like and we're hunting for one more builder to help us rewrite the rules of software quality.
Why This Role is Different
Most "AI engineer" jobs are just applying models someone else built. This isnât that. This is about pushing RL to its edge:
- Agents that think: networks that see and understand apps through vision, structure, and behavior.
- Agents that explore: curiosity-driven RL that uncovers edge cases no human would think of.
- Agents that learn: smarter with every bug, sharper with every correction.
- Agents that scale: millions of states, thousands of sessions, decisions in sub-seconds.
If youâve ever wanted to take RL out of papers and into the wild, this is it.
What Youâll Achieve
In your first three months, youâll see your reinforcement learning prototypes running live inside real applications, surfacing bugs no human ever noticed. By six months, those agents will have evolved, scaling across multiple environments, learning and adapting in ways that prove this isnât theory but reality. And within a year, the intelligence youâve built will sit at the heart of every release for our first customers, powering their ability to ship AI-generated code with confidence.
What You Bring (NonâNegotiables)
- 5+ years shipping ML to production (real systems, not papers).
- Deep RL expertise, you think in Qâvalues and policy gradients.
- Experience building autonomous agents that actually work at scale.
- Python/PyTorch mastery.
The Stuff That Matters
- Youâre obsessed with solving "impossible" problems.
- Youâd rather ship and learn than debate in theory.
- You can explain RL to a CEO and optimize it for a GPU cluster.
- You thrive in chaos and see it as opportunity.
Why Join Now
Impact: You wonât be "joining a team." Youâll be the team that defines how software is built in the age of AI. Your code wonât sit in a corner, it will become the backbone of a new category.
Market: Software testing hasnât changed in 30 years. AIâgenerated code has rewritten the rules overnight. Whoever solves this bottleneck doesnât just win a market, they reshape the entire industry.
Team: Small, elite, no passengers. Youâll be working side by side with a CTO who built this at Meta and a founding team thatâs scaled some of the fastestâgrowing tech companies on the planet.
Timing: Rarely do technology shifts and career timing line up. This is one of those moments. Five years from now, autonomous QA will be a given. Right now, itâs unsolved, and you could be the one who solves it.
The Challenge
Big tech tried to bruteâforce this problem and hit a wall. Most startups never got past brittle scripts. The reason is simple: building true autonomy takes more than patching frameworks, it takes intelligence. Thatâs the path weâre on. Your system will need to:
- Navigate the chaos of modern web apps.
- Learn from sparse, delayed rewards.
- Balance exploration with validation.
- Transfer knowledge across completely different applications.
It wonât be easy. Thatâs the point.
What You Get
- Equity that actually moves the needle, not token options, but a real ownership stake in what could be the categoryâdefining AI company of the decade.
- Unlimited firepower, the hardware, compute, and resources you need to push RL further than anyone has before.
- A seat at the table, not a cog in the machine, youâll be in the room where every decision is made, shaping both the product and the company.
- Speed over politics, a London base where execution beats process, every time.
- A shot at legacy, work that will outlive your CV, the kind of achievement youâll still be talking about 20 years from now.
To win the space, weâre looking for the best people in London, with 10/10 ambition and work ethic to join us and build a product people love.
Senior AI Engineer - Reinforcement Learning Lead in London employer: Duku AI
Contact Detail:
Duku AI Recruiting Team
StudySmarter Expert Advice đ¤Ť
We think this is how you could land Senior AI Engineer - Reinforcement Learning Lead in London
â¨Tip Number 1
Network like a pro! Get out there and connect with folks in the AI and tech scene. Attend meetups, webinars, or even just grab a coffee with someone in the industry. You never know who might have the inside scoop on job openings or can put in a good word for you.
â¨Tip Number 2
Show off your skills! Create a portfolio showcasing your reinforcement learning projects. Whether it's GitHub repos or a personal website, let your work speak for itself. This is your chance to demonstrate that you can push RL to its edge and solve those 'impossible' problems.
â¨Tip Number 3
Prepare for interviews like itâs game day! Research the company, understand their products, and be ready to discuss how your experience aligns with their mission. Practice explaining complex concepts in simple terms â you might need to break down RL for a non-technical audience!
â¨Tip Number 4
Donât forget to apply through our website! Itâs the best way to ensure your application gets seen by the right people. Plus, we love seeing candidates who are proactive and engaged. So, hit that apply button and show us what youâve got!
We think you need these skills to ace Senior AI Engineer - Reinforcement Learning Lead in London
Some tips for your application đŤĄ
Show Your Passion for AI: When you're writing your application, let your enthusiasm for AI and reinforcement learning shine through. We want to see that youâre not just ticking boxes but genuinely excited about pushing the boundaries of what's possible in this field.
Be Specific About Your Experience: Donât just list your past roles; dive into the details! Share specific projects where you've shipped ML to production and how you tackled challenges. We love seeing real-world examples of your deep RL expertise and how you've built autonomous agents that work at scale.
Tailor Your Application: Make sure your application speaks directly to the role. Highlight your Python/PyTorch mastery and any experience with curiosity-driven RL. Weâre looking for someone who can explain complex concepts simply, so show us you can do that!
Apply Through Our Website: We encourage you to apply directly through our website. Itâs the best way for us to see your application in the right context. Plus, it shows youâre serious about joining our team and being part of this exciting journey!
How to prepare for a job interview at Duku AI
â¨Know Your Reinforcement Learning Inside Out
Make sure you can discuss reinforcement learning concepts fluently, especially Q-values and policy gradients. Prepare to explain how you've applied these in real-world scenarios, as this role demands deep expertise.
â¨Showcase Your Problem-Solving Skills
Be ready to share specific examples of 'impossible' problems you've tackled in the past. Highlight your experience with building autonomous agents and how you've navigated challenges in scaling them.
â¨Demonstrate Your Passion for AI
Express your enthusiasm for pushing the boundaries of AI and RL. Talk about any personal projects or research that align with the company's mission to redefine software quality through AI.
â¨Prepare for Technical Challenges
Expect to face technical questions or coding challenges during the interview. Brush up on Python and PyTorch, and be prepared to demonstrate your coding skills in a practical setting.