Machine Learning Engineer (Genai & Nlp)

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). Nice to have: Experience with Databricks. 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. Location: Barcelona. (Hybrid: 1-2 days in the office). Language: English C1 (Fluent, all team communication is in English).

Why CAPITOLE? An individual training budget of €1,200 for whatever you choose: events, books, certifications or courses. Monthly check-ins with your team for continuous feedback. Flexible working hours to balance your professional and personal life. Private health insurance fully paid by Capitole. Flexible compensation: meal, transport and/or childcare vouchers. WellHub (Gymforless). Discounts on major brands for employees (Club Capitole). Don’t know us yet? Come discover us! ( See what people say about us Glassdoor ( Capitole | Empowering people, unlocking technology innovation

Capitole keeps growing - and we want to do it with you! We’re looking for an AI/ML Engineer to join a global leader in HR technology - a team building Generative AI assistants used across global markets. This is a hands-on engineering role, where focus is shipping GenAI/NLP models to production in Python, working shoulder-to-shoulder with MLEs inside a lean 5-6 person squad across 3-4 projects. If you code your ML solutions yourself rather than leaning on out-of-the-box AutoML tools, and you like owning the technical solution end-to-end, this is for you. What you’ll find here: 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).