Machine Learning Engineer, Personalization

Job Description:

Machine Learning Engineer Personalization
Dow Jones Job Location: Barcelona

About the Team:
Our Technology team drives the evolution of our 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 AIleveraging 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 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.

You Have:

• 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.
  

Our Benefits:

• Comprehensive Healthcare Plans for you and your family (paid by Dow Jones)
• Extra paid Time Off (30 days of holidays/year)
• Possibility to work remotely for 3 months/year (desplazamiento program) or one week of remote work per quarter
• Meal benefit with Pluxee (171/month on top of your salary)
• Retirement Plans (Dow Jones will pay 2% of a members Pensionable Salary and match employee contribution up to a maximum of 3 %).
• Comprehensive Insurance Plans
• Well-being Resources (200 USD allowance per quarter Classpass etc.)
• Family Care Benefits & Caregiving Support
• Subscription Discounts
• Employee Referral Program

Equal Opportunity Employer

Reasonable Accommodation

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Were committed to offering competitive and flexible compensation to attract top talent. This pay range reflects our good faith estimate for the role and may vary based on a candidates experience skills location and other relevant factors.

For bonus-eligible roles targets are determined based on multiple considerations including market benchmarks and individual contributions.

For benefits-eligible roles we offer a comprehensive and competitive benefits package covering health retirement wellbeing and more along with optional benefits to meet the diverse needs of our employees.