Senior ML Engineer: Agentic AI for Personalised Learning

Busuu; Comunidad de Madrid; Híbrido; EUR 70.000 - 90.000; Jornada completa

Ventajas ofrecidas por este puesto de trabajo

Free breakfast

2 free lunches per week

Private health insurance

Training budget

Hybrid work model

Maternity/Paternity leave

Social events

Descripción de la vacante

Busuu is seeking a Senior Machine Learning / AI Engineer to design, build, and deploy agentic AI systems powering adaptive learning experiences. You will work with LangChain/LangGraph, LLMs, and RAG to shape personalized paths and content generation.

You will own end-to-end ML lifecycle, build scalable pipelines, and collaborate with Data Scientists, ML Engineers and product teams to improve experimentation velocity and user outcomes.

Formación

• Strong foundations in ML and AI with software engineering experience.
• Proven experience deploying agentic AI systems in production.
• Proficiency building data and training pipelines end-to-end.
• Hands-on with NLP, personalization and evaluation.
• Experience with LangChain / LangGraph and LLM-driven features.

Responsabilidades

• Own design, development and deployment of production-grade agentic AI systems.
• Architect LLM-powered features and RAG-based solutions for learning paths.
• Lead multi-agent workflows and orchestration patterns.
• Move models from experimentation to production with reliable pipelines.
• Improve ML infra and tooling to speed and safeguard AI development.

Conocimientos

Python

ML pipelines

LangChain

LangGraph

LLMs

Prompt engineering

Vector stores

NLP

Herramientas

SQL

Airflow

SageMaker

Lambda

S3

Kubernetes

MLFlow

Descripción del empleo

Busuu is seeking a Senior Machine Learning / AI Engineer to design, build, and deploy agentic AI systems powering adaptive learning experiences. You will work with LangChain/LangGraph, LLMs, and RAG to shape personalized paths and content generation.

You will own end-to-end ML lifecycle, build scalable pipelines, and collaborate with Data Scientists, ML Engineers and product teams to improve experimentation velocity and user outcomes.