Senior Applied AI Scientist — Hybrid (50% Remote)

Bertelsmann-Jobs

Barcelona

Hybrid

EUR 70,000 - 95,000

Full time

5 days ago

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Benefits offered by this job

50% remote working model

Offices in city centre

Reduced hours on Fridays and holidays

Company mobile phone

e-book and audiobook app access

More annual leave than required

Job summary

Penguin Random House Grupo Editorial, a Spanish-language division of Penguin Random House and part of Bertelsmann, seeks a Senior Data Scientist – Applied AI in Barcelona. You’ll lead AI initiatives across NLP and generative AI, building scalable Python services and collaborating with ML and Infrastructure engineers to deliver reliable AI-powered products.

You’ll contribute to responsible AI practices, work with global teammates, and thrive in a people-centered culture that values collaboration,

Qualifications

5+ years of professional experience in data science, machine learning, applied AI or a related technical discipline.
Advanced Python skills and the software engineering practices needed to build maintainable production code.
Strong foundations in machine learning and data science, including model development, experimentation and evaluation.
Practical experience building with large language models and generative AI.
Understanding of modern LLM application patterns, including prompting, structured outputs, embeddings, retrieval/RAG and tool or function calling.
Experience designing robust approaches to model evaluation and interpreting results critically.
Strong SQL and experience working with substantial datasets.
Experience with cloud environments and modern data platforms.
Experience building or integrating APIs, services or data pipelines.
The ability to move comfortably between experimentation and engineering, rather than stopping at a successful notebook or proof of concept.
Strong problem‑solving skills and the confidence to make technical decisions when the path isn’t obvious.
The ability to communicate clearly with both technical and non‑technical colleagues.
A high level of professional English, as much of your collaboration will be with international teams.

Responsibilities

Lead data science and applied AI work from exploration and experimentation through to production.
Develop and evaluate machine learning, NLP and generative AI solutions, selecting the approach that best fits the problem.
Build applications using LLMs and techniques such as structured generation, embeddings, semantic search, retrieval, RAG, tool use and agents.
Develop production‑quality Python services, APIs and data pipelines that integrate models and AI capabilities into real products and workflows.
Design experiments and evaluation frameworks to compare approaches, measure quality and understand where systems succeed and fail.
Work with structured and unstructured data at scale using SQL and modern data platforms.
Collaborate with ML and Infrastructure Engineers on deployment, containerization, monitoring and production operations.
Work directly with colleagues across the business to turn open-ended questions into practical technical solutions.
Support other Data Scientists and contribute to shared technical standards, reusable components and best practices.
Collaborate with Data Science & AI colleagues globally, while staying current with developments in machine learning and AI and helping identify which new approaches are worth adopting.