Machine Learning Engineer

Capitole
A Coruña, Spain
3 days ago
Apply on www.buscojobs.com.es
Prepare application

Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Experience required
1 year minimum
Working hours
Regular working hours
Languages
English

Tech stack

Artificial Intelligence Amazon Web Services Amazon S3 Continuous Integration Python (Programming Language) Machine Learning Software Engineering Data Processing Pytorch Large Language Models Generative AI Git
+3 more
Pandas Scikit Learn Docker

Job description

Capitole keeps growing - and we want to do it with you!¡Inscríbase sin demora!Se espera un gran volumen de solicitantes para el puesto que se detalla a continuación, no espere para enviar su CV.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).We’re looking for someone who: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).xbhjioeDon’t know us yet?Come discover us!()See what people say about us Glassdoor ()Capitole Empowering people, unlocking technology innovation Hay opciones de teletrabajo/trabajo desde casa disponibles para este puesto.

Requirements

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). We’re looking for someone who: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).

Benefits & conditions

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). xbhjioeDon’t know us yet? Come discover us! ()See what people say about us Glassdoor ()Capitole | Empowering people, unlocking technology innovation Hay opciones de teletrabajo/trabajo desde casa disponibles para este puesto.

Apply for this position

This job is hosted externally. Click below to view the full posting and apply.

Apply on www.buscojobs.com.es
Prepare application

Good distractions

Talks and stories from around this role — technically off-topic, practically not.

6:21 min

Investigating push inefficiencies with upstream Git experts

Jonathan Creamer · Coffee With Developers

2:03 min

Accelerating pandas dataframes using cudf module plugins

Ankit Patel Ankit Patel · World Congress 2024

2:07 min

Inspecting default bridge architectures and custom Docker networks

Oliver Seitz Oliver Seitz · World Congress 2025

2:08 min

Essential engineering roles in the generative AI space

Mary Grygleski Mary Grygleski · LIVE

56 sec

Favorite git commands and the importance of patch commits

Eileen Uchitelle Eileen Uchitelle +1 · Coffee With Developers

3:22 min

Evaluating advanced artificial intelligence platforms for daily recruitment

Rudi Bauer Rudi Bauer +1 · Cappuccino with HR

Videos

See all

Related articles

See all