Dow Jones
Technology
MachineLearningEngineer,Personalization
Neural analysis suggests this role is
optimal for Senior candidates.
“Machine Learning Engineer, Personalization at Dow Jones. Skills: Machine Learning, personalization systems, recommender systems, ranking systems, Python. 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”
What You'll Achieve.
deliver highly relevant, personalized experiences across our digital products; connect users with the most relevant content; serve personalized content to millions of readers in real time
Industry & Context.
What They're Looking For.
Must Have
3+ years of industry experience applying machine learning methods, with a focus on recommender systems, search, ranking, or personalization, proficiency in Python for production ML systems, Experience with A 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 You'll Do.
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 architectures
and user/content signals
Drive experimentation and A testing to measure impact and iterate on models and features
Leverage LLMs to enhance content understanding and feature extraction
Optimize systems for performance
and scalability across high-traffic environments
Contribute to engineering best practices
Collaborate with product managers
and analysts to translate business needs into scalable technical solutions
How You'll Work.
Team & Collaboration
Partner closely with product, data science, and engineering teams; Collaborate with product managers, data scientists, and analysts
Full Job Description
## **Job Description:** **Machine Learning Engineer, Personalization** Dow Jones Job Location: Barcelona Job ID ITD5035 - Sr Software Engineer **About the Team:** Our Technology team drives the evolution of our Technology, Engineering, Data, Product and User Experience functions. With a keen focus on delivering cutting-edge solutions, we shape the digital landscape for our customers, readers and users. From revolutionizing visuals to optimizing tools and harnessing the power of data, mobile, video and social platforms, our team is committed to providing a seamless and immersive experience across all touchpoints. Collaborating closely with our newsrooms and strategic partners, we spearhead the development of groundbreaking products and technologies. **About the Role:** 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. ** You Will:** * 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 architectures, and user/content signals. * Drive experimentation and A/B testing to measure impact and iterate on models and fea
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