Machine Learning Engineer (Personalization)

Dow Jones (Barcelona, Spain) Follow 2 days ago

Full-time SQL Feature Extraction NoSQL Machine Learning Python

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Requirements
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3+ years of industry experience applying machine learning methods, with a strong focus on recommender systems, search, ranking, or personalization
Strong proficiency in Python for production ML systems
Experience with A/B testing and experimentation frameworks to measure model impact
Familiarity with cloud platforms (AWS, GCP, or Azure) and containerized environments
Familiarity with SQL and NoSQL databases
Degree in computer science, machine learning, statistics, or equivalent work experience

What the job involves

We are looking for a Senior Machine Learning Engineer to join our Personalization team in Barcelona
You will design and build systems that deliver highly relevant, personalized experiences across our digital products
This role sits at the intersection of backend engineering, data, and applied AI—leveraging modern architectures and machine learning techniques to connect users with the most relevant content
You will play a key role in building scalable indexing, retrieval and ranking systems that serve personalized content to millions of readers in real time
You will partner closely with product, data science, and engineering teams, bringing technical depth and sound judgment to architectural decisions, model design, and evaluation methodology
Design, build, and operate personalization systems and services powering content discovery and user engagement
Develop and improve ML models across the whole personalization stack, from candidate generation to final ranking
Use data-driven methods to improve candidate retrieval, leveraging embeddings, two-tower xqbhyrx architectures, and user/content signals
Drive experimentation and A/B testing to measure impact and iterate on models and features
Leverage LLMs to enhance content understanding and feature extraction
Optimize systems for performance, latency, and scalability across high-traffic environments
Contribute to engineering best practices, including testing, observability, and CI/CD
Collaborate with product managers, data scientists, and analysts to translate business needs into scalable technical solutions