Senior AI Engineer - Reinforcement Learning Lead
Senior AI Engineer - Reinforcement Learning Lead

Senior AI Engineer - Reinforcement Learning Lead

Full-Time 72000 - 108000 ÂŁ / year (est.) No home office possible
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At a Glance

  • Tasks: Lead the development of cutting-edge reinforcement learning agents that redefine software quality.
  • Company: Join a venture-backed AI company transforming software testing with autonomous agents.
  • Benefits: Equity stake, unlimited resources, and a fast-paced, innovative work environment.
  • Why this job: Make a real impact by solving complex problems and shaping the future of AI in software.
  • Qualifications: 5+ years in ML production, deep RL expertise, and Python/PyTorch mastery required.
  • Other info: Work alongside elite tech leaders in a dynamic, opportunity-rich environment.

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 isn’t 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 you’ve ever wanted to take RL out of papers and into the wild, this is it.

What You’ll Achieve

In your first three months, you’ll 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 isn’t theory but reality. And within a year, the intelligence you’ve 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 (Non‑Negotiables)

  • 5+ years shipping ML to production (real systems, not papers).
  • Deep RL expertise, you think in Q‑values and policy gradients.
  • Experience building autonomous agents that actually work at scale.
  • Python/PyTorch mastery.

The Stuff That Matters

  • You’re obsessed with solving “impossible” problems.
  • You’d 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 won’t be “joining a team.” You’ll be the team that defines how software is built in the age of AI. Your code won’t sit in a corner, it will become the backbone of a new category.
  • Market: Software testing hasn’t changed in 30 years. AI‑generated code has rewritten the rules overnight. Whoever solves this bottleneck doesn’t just win a market, they reshape the entire industry.
  • Team: Small, elite, no passengers. You’ll be working side by side with a CTO who built this at Meta and a founding team that’s scaled some of the fastest‑growing 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, it’s unsolved, and you could be the one who solves it.

The Challenge

Big tech tried to brute‑force 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. That’s the path we’re 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 won’t be easy. That’s the point.

What You Get

  • Equity that actually moves the needle, not token options, but a real ownership stake in what could be the category‑defining 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, you’ll 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 you’ll still be talking about 20 years from now.

To win the space, we’re 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 employer: Duku AI

At Duku AI, we are redefining the future of software quality with cutting-edge reinforcement learning technology. Our vibrant London-based team thrives on innovation and collaboration, offering unparalleled opportunities for personal and professional growth in a fast-paced environment. Join us to make a significant impact, where your contributions will directly shape the next generation of autonomous QA solutions and be rewarded with meaningful equity and resources.
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Contact Detail:

Duku AI Recruiting Team

StudySmarter Expert Advice 🤫

We think this is how you could land Senior AI Engineer - Reinforcement Learning Lead

✨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.

✨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 your expertise and passion for pushing RL to its limits.

✨Tip Number 3

Prepare for those interviews! Research common questions for AI engineers and practice your responses. Be ready to discuss your experience with Python and PyTorch, and how you've tackled complex problems in the past. Confidence is key!

✨Tip Number 4

Apply through our website! We love seeing candidates who are genuinely interested in joining us at Duku AI. Tailor your application to highlight how your skills align with our mission to revolutionise software quality. Let's build something amazing together!

We think you need these skills to ace Senior AI Engineer - Reinforcement Learning Lead

Reinforcement Learning (RL)
Deep RL expertise
Q-values and policy gradients
Building autonomous agents
Python mastery
PyTorch mastery
Machine Learning (ML) production experience
Problem-solving skills
Explaining complex concepts to non-technical stakeholders
Optimising for GPU clusters
Adaptability in chaotic environments
Curiosity-driven exploration
Knowledge transfer across applications

Some tips for your application 🫡

Show Your Passion for AI: When you write your application, let your enthusiasm for AI and reinforcement learning shine through. We want to see that you’re not just ticking boxes but genuinely excited about pushing the boundaries of what's possible in this field.

Be Specific About Your Experience: Don’t just list your skills; give us concrete examples of how you've applied them in real-world scenarios. Talk about the projects you've worked on, the challenges you faced, and how you overcame them. This helps us see your problem-solving mindset in action!

Tailor Your Application: Make sure your application speaks directly to the role. Highlight your deep RL expertise and experience with autonomous agents. Show us that you understand what we’re building and how your background fits into our mission to redefine software quality.

Apply Through Our Website: We encourage you to apply directly through our website. It’s the best way for us to receive your application and ensures you don’t miss out on any important updates. Plus, it shows us you’re keen to be part of our journey from the get-go!

How to prepare for a job interview at Duku AI

✨Know Your Reinforcement Learning Inside Out

Make sure you can discuss reinforcement learning concepts fluently. Be prepared to explain Q-values, policy gradients, and how you've applied these in real-world scenarios. The interviewers will want to see your depth of knowledge and practical experience.

✨Showcase Your Problem-Solving Skills

Prepare examples of 'impossible' problems you've tackled in the past. Highlight your thought process and how you approached these challenges. This role is all about pushing boundaries, so demonstrating your ability to think outside the box will impress the team.

✨Demonstrate Your Coding Mastery

Brush up on your Python and PyTorch skills before the interview. You might be asked to solve coding problems or discuss your previous projects. Be ready to showcase your coding style and efficiency, as well as how you optimise for performance.

✨Understand the Company’s Vision

Familiarise yourself with Duku AI's mission and the challenges they aim to solve in software testing. Show enthusiasm for their vision and be ready to discuss how your skills align with their goals. This will demonstrate your genuine interest in the role and the company.

Senior AI Engineer - Reinforcement Learning Lead
Duku AI
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  • Senior AI Engineer - Reinforcement Learning Lead

    Full-Time
    72000 - 108000 ÂŁ / year (est.)
  • D

    Duku AI

    50-100
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