Machine Learning Engineer (Genai & Nlp)

Brings3-5 yearsof experience buildingproduction features/systems with AI/ML . Writesadvanced, production-grade Python- not notebook scripting. Has worked onreal NLP / GenAI / LLM projectsand can explain them in depth - embeddings, evaluation metrics beyond accuracy, how they assessed system performance. Thinks like anML engineer : moves models to production, understands the full pipeline, applies solid coding practices ( Git, PR, CI/CD, Docker ). Knows their way aroundML libraries(scikit-learn, PyTorch) anddata processing(pandas). ?Nice to have: Experience withDatabricks. Familiarity withAWS infrastructure(S3, Lambda, Bedrock). Understanding ofdata augmentation, bias and training pipelines . ASoftware Engineeringbackground 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 usGlassdoor ( )Capitole | Empowering people, unlocking technology innovation

Capitole keeps growing - and we want to do it with you! We’re looking for anAI/ML Engineerto join a global leader in HR technology - a teambuilding Generative AI assistantsused across global markets.This is ahands-on engineering role , where focus isshipping GenAI/NLP models to productioninPython , 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: Buildingproduction-ready GenAI/LLM features- chatbot assistants and NLP systems, from prototype to production. Writingstructured, quality Pythonwith real engineering discipline:PR practices, Git, CI/CD, Docker . Designingend-to-end NLP pipelines- data processing, model development, evaluation, deployment. Getting hands-on withLLMs, embeddings and modern GenAI tooling(OpenAI, AWS Bedrock).