Machine Learning Engineering

Building production-ready GenAI/LLM features - chatbot assistants and NLP systems, from prototype to production.Writing structured, quality Python with real engineering discipline: PR practices, Git, CI/CD, Docker.Designing end-to-end NLP pipelines - data processing, model development, evaluation, deployment.Getting hands-on with LLMs, embeddings and modern GenAI tooling (OpenAI, AWS Bedrock). Brings 3-5 years of experience building production features/systems with AI/ML.Writes advanced, production-grade Python - not notebook scripting.Has worked on real NLP / GenAI / LLM projects and can explain them in depth - embeddings, evaluation metrics beyond accuracy, how they assessed system performance.Thinks like an ML engineer: moves models to production, understands the full pipeline, applies solid coding practices (Git, PR, CI/CD, Docker). Knows their way around ML libraries (scikit-learn, PyTorch) and data processing (pandas). Familiarity with AWS infrastructure (S3, Lambda, Bedrock). Understanding of data augmentation, bias and training pipelines.A Software Engineering background with a recent move into AI/ML.Hybrid: 1-2 days in the office). Language: English C1 (Fluent, all team communication is in English).

An individual training budget of €1,200 for whatever you choose: events, books, certifications or courses.Flexible working hours to balance your professional and personal life.Private health insurance fully paid by Capitole.Discounts on major brands for employees (Club Capitole). Capitole | Empowering people, unlocking technology innovationHay opciones de teletrabajo/trabajo desde casa disponibles para este puesto.