Senior ML Engineer, Personalization & Search - Hybrid (Barcelona)

Dow Jones Company; Barcelona; Hybrid; EUR 70,000 - 110,000; Full time

Benefits offered by this job

Healthcare plans

Remote work up to 3 months

Meal benefit with Pluxee

Retirement plan

Wellbeing allowance

Learning courses

Employee referral program

Job summary

Dow Jones is seeking a Senior Machine Learning Engineer to join our Search team in Barcelona. You will design and build scalable systems delivering personalized content experiences across our digital products.

Collaborating with product, data science, and engineering teams, you will advance search indexing, retrieval and ranking, apply ML models, and leverage embeddings and LLMs to optimize performance in a high-traffic environment.

Qualifications

• 2-4 years of industry experience applying machine learning methods, with focus on recommender systems, search, ranking, or personalization.
• Proficient in Python for production ML systems and data-driven evaluation.

Responsibilities

• Design, build, and operate search systems powering content discovery.
• Develop ML models across the personalization stack from candidate generation to ranking.
• Improve candidate retrieval using embeddings, two-tower architectures, and signals.
• Lead A/B experiments to measure impact and iterate on models.
• Leverage LLMs to enhance content understanding and feature extraction.
• Optimize performance, latency, and scalability in high-traffic environments.
• Collaborate with product, data science, and engineering to translate business needs into scalable solutions.

Skills

Python for ML

Recommender systems

A/B testing

Cloud platforms

SQL/NoSQL

Education

Bachelor's degree in CS or related

Job description

Dow Jones is seeking a Senior Machine Learning Engineer to join our Search team in Barcelona. You will design and build scalable systems delivering personalized content experiences across our digital products.

Collaborating with product, data science, and engineering teams, you will advance search indexing, retrieval and ranking, apply ML models, and leverage embeddings and LLMs to optimize performance in a high-traffic environment.