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:
1. Design, build, and operate personalization systems and services powering content discovery and user engagement.
2. Develop and improve ML models across the whole personalization stack, from candidate generation to final ranking.
3. Use data-driven methods to improve candidate retrieval, leveraging embeddings, two-tower architectures, and user/content signals.
4. Drive experimentation and A/B testing to measure impact and iterate on models and features.
5. Leverage LLMs to enhance content understanding and feature extraction.
6. Optimize systems for performance, latency, and scalability across high-traffic environments.
7. Contribute to engineering best practices, including testing, observability, and CI/CD.
8. Collaborate with product managers, data scientists, and analysts to translate business needs into scalable technical solutions.
You Have:
9. 3+ years of industry experience applying machine learning methods, with a strong focus on recommender systems, search, ranking, or personalization.
10. Strong proficiency in Python for production ML systems.
11. Experience with A/B testing and experimentation frameworks to measure model impact.
12. Familiarity with cloud platforms (AWS, GCP, or Azure) and containerized environments.
13. Familiarity with SQL and NoSQL databases.
14. Degree in computer science, machine learning, statistics, or equivalent work experience.
Our Benefits:
15. Comprehensive Healthcare Plans for you and your family (paid by Dow Jones)
16. Extra paid Time Off (30 days of holidays/year)
17. Possibility to work remotely for 3 months/year (desplazamiento program) or one week of remote work per quarter
18. Meal benefit with Pluxee (171€/month on top of your salary)
19. Retirement Plans (Dow Jones will pay 2% of a members Pensionable Salary and match employee contribution up to a maximum of 3 %).
20. Comprehensive Insurance Plans
21. Well-being Resources (200 USD allowance per quarter, Classpass, etc.)
22. Family Care Benefits & Caregiving Support
23. Subscription Discounts
24. Employee Referral Program
Equal Opportunity Employer
All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, age, national origin, protected veteran status, disability status or any other protected characteristic. We strongly encourage applications from all qualified individuals, including women, people with disabilities, and those from underrepresented groups.
Reasonable Accommodation
We are committed to providing reasonable accommodation for qualified individuals with disabilities in our job application and/or interview process.