Machine Learning Engineer
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Role details
Tech stack
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Job description
| Capitole keeps growing - and we want to do it with you!We’re looking for anMachine Learning Engineer#MLEto 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 likeowning 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 prototypeto production).Writingstructured, quality Pythonwith real engineering discipline:PR practices, Git, CI/CD, Docker.Getting hands-on withLLMs, embeddings and modern GenAI tooling(OpenAI, AWS Bedrock).We’re looking for someone who: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).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.Flexible compensation: meal, transport and/or childcare vouchers.Discounts on major brands for employees (Club Capitole).Capitole | Empowering people, unlocking technology innovation#J-*****-Ljbffr |
Requirements
Experience with Databricks. Familiarity with AWS infrastructure (S3, Lambda, Bedrock). Understanding of data augmentation, bias and training pipelines, English C1 (Fluent, all team communication is in English).
Benefits & conditions
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. Flexible compensation: meal, transport and/or childcare vouchers. Discounts on major brands for employees (Club Capitole). Capitole | Empowering people, unlocking technology innovation #J-*****-Ljbffr
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