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Software Engineer - Machine Learning at Duku AI
London, England, United Kingdom -
Full Time

Start Date

Immediate

Expiry Date

21 Jun, 26

Salary

0.0

Posted On

23 Mar, 26

Experience

2 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

No

Skills

Python, TypeScript, Cloud Infra, LLM-Powered Testers, LangChain, Vector Stores, Prompt Engineering, Frontend, Backend, Infra, AI Agents, Retrieval Pipelines, Model Experimentation, Embedding Experimentation

Industry

technology;Information and Internet

Description
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 Full-stack firepower : Frontend, backend, infra, no silos Product obsession : You care more about outcomes than outputs Experimental instinct: You build → test → learn → repeat 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.
Responsibilities
The role involves designing and training AI agents powered by LLMs to act as testers that learn and adapt in real time, while owning the full stack from Python/TypeScript code to cloud infrastructure deployment. Responsibilities also include turning prototypes into production by running real experiments on models, embeddings, and retrieval pipelines.