We're partnering with a fast-growing consumer technology business that is leveraging cutting-edge AI to transform how millions of users learn, engage, and interact with digital products worldwide.
This is an opportunity to join a highly ambitious AI team at a pivotal stage of growth, helping shape the next generation of intelligent, personalised user experiences. You'll be working on real-world, large-scale AI challenges, building production-ready systems that directly impact millions of users globally.
The Opportunity
As a Senior Machine Learning / AI Engineer, you'll take ownership of designing and deploying advanced AI systems, helping drive the company's AI strategy while working closely with product, data, and engineering teams.
This is a hands-on role for someone who enjoys moving between research, experimentation, and production, and wants to work on some of the most exciting developments in agentic AI, LLMs, and personalisation.
What You'll Be Doing
Designing, building, and scaling production-grade agentic AI systems




Developing multi-agent workflows using frameworks such as LangChain and LangGraph
Architecting and deploying LLM-powered applications using RAG, vector databases, and prompt engineering techniques
Building intelligent systems that can reason, plan, and act autonomously
Taking ML models from experimentation through to production deployment and monitoring
Driving improvements across AI infrastructure, tooling, and development workflows
Collaborating closely with Product, Engineering, Data Science, and Design teams to deliver impactful AI-driven experiences
Evaluating emerging AI technologies and helping shape technical strategy across the organisation
Contributing to best practices around AI engineering, experimentation, and model evaluation
What We're Looking For
Strong experience in Machine Learning, AI Engineering, or Applied AI roles
Excellent Python software engineering skills
Proven experience building and deploying LLM-powered applications

📌 AI Engineer (Madrid)
🏢 Trust In SODA
📍 Madrid