At a Glance
- Tasks: Develop AI-driven software that transforms quality assurance and enhances engineering velocity.
- Company: Join a venture-backed startup led by industry veterans from Meta, Uber, and Deliveroo.
- Benefits: Competitive salary, flexible work environment, and opportunities for rapid professional growth.
- Other info: Dynamic startup culture with a focus on experimentation and high ownership.
- Why this job: Be part of a revolutionary team shaping the future of autonomous testing in software.
- Qualifications: Experience in AI/LLMs, full-stack development, and a passion for innovative product outcomes.
The predicted salary is between 36000 - 60000 € per year.
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.
What You’ll Do
- Ship fast, learn faster: We deploy daily, not monthly
- Talk to users, shape the roadmap: Sit in the trenches with founders on calls that define what we build
- Train AI agents: Design LLM-powered testers that explore, learn, and adapt in real time
- Own the stack: Python, TypeScript, cloud infra, from commit to production
- Turn prototypes into production: Run real experiments on models, embeddings, and retrieval pipelines
What We’re Looking For
- Relentless drive: You execute fast, adapt faster
- Startup scar tissue: You’ve shipped product with no safety net
- Fluency with AI/LLMs: LangChain, vector stores, prompt engineering
- Product obsession: You care more about outcomes than outputs
Ideal Background
There’s no perfect pedigree. We hire for mindset, not credentials. That said, you might have:
- Shipped AI features in prod
- Built something from 0 to 1
- Thrived in chaos with high ownership
Why This Matters
Software is accelerating. QA hasn’t kept up. Autonomous testing is inevitable, and we’re building it.
Five years from now, every high‑velocity team will rely on AI agents like ours to ship faster, safer, and smarter.
Join now, and help make that future real, before someone else does.
Software Engineer - Machine Learning employer: Duku AI
At Duku AI, we are not just redefining software quality; we are creating a vibrant work culture that thrives on innovation and collaboration. As a Software Engineer in Machine Learning, you will be part of a dynamic team that values your input and encourages rapid learning and growth, all while working in a fast-paced startup environment. With daily deployments and the opportunity to shape the future of autonomous testing, you'll find meaningful challenges and the chance to make a significant impact in the tech landscape.
StudySmarter Expert Advice🤫
We think this is how you could land Software Engineer - Machine Learning
✨Tip Number 1
Network like a pro! Reach out to folks in the industry, especially those who work at Duku AI or similar companies. A friendly chat can open doors and give you insights that a job description just can't.
✨Tip Number 2
Show off your skills! Create a portfolio or GitHub repo showcasing your projects, especially those involving AI and machine learning. This is your chance to demonstrate your full-stack firepower and product obsession.
✨Tip Number 3
Prepare for the interview by understanding their tech stack. Brush up on Python, TypeScript, and cloud infrastructure. Being fluent in these areas will show you're ready to own the stack and contribute from day one.
✨Tip Number 4
Apply through our website! It’s the best way to ensure your application gets seen. Plus, it shows you’re genuinely interested in being part of our mission to change software forever.
We think you need these skills to ace Software Engineer - Machine Learning
Some tips for your application 🫡
Show Your Passion for AI:When writing your application, let your enthusiasm for AI and machine learning shine through. We want to see how you’ve engaged with these technologies in the past and how you envision using them to change software quality.
Highlight Your Startup Experience:If you've thrived in a startup environment before, make sure to mention it! Share specific examples of how you’ve shipped products quickly and adapted to challenges without a safety net. We love that kind of grit!
Be Clear About Your Skills:We’re looking for full-stack firepower, so don’t be shy about showcasing your skills in Python, TypeScript, and cloud infrastructure. Be specific about your experience and how you’ve used these tools to solve real problems.
Apply Through Our Website:We encourage you to apply directly through our website. It’s the best way for us to see your application and get to know you better. Plus, it shows you’re serious about joining our mission to revolutionise software testing!
How to prepare for a job interview at Duku AI
✨Know Your Tech Stack
Make sure you’re well-versed in Python, TypeScript, and cloud infrastructure. Brush up on your full-stack knowledge, as they’ll likely ask you about your experience with both frontend and backend development.
✨Show Your Experimental Mindset
Prepare to discuss your past projects where you built, tested, and learned from your experiments. They want to see that you have a hands-on approach and can adapt quickly in a fast-paced environment.
✨Understand AI and LLMs
Familiarise yourself with concepts like LangChain, vector stores, and prompt engineering. Be ready to explain how you’ve used these technologies in previous roles or how you would apply them in this position.
✨Demonstrate Product Obsession
Be prepared to talk about how you prioritise outcomes over outputs. Share examples of how you’ve engaged with users to shape product roadmaps and how that has influenced your work.
