machine learning engineer

Enfint; Barcelona; Presencial; EUR 60.000 - 90.000; Jornada completa

Ventajas ofrecidas por este puesto de trabajo

Healthcare for employee and family

30 days paid holidays

Remote work 3 months per year

Meal benefit

Retirement plan contributions

Comprehensive insurance plans

Well-being resources

Family care benefits

Subscription discounts

Employee referral program

Descripción de la vacante

Dow Jones ищет инженера по машинному обучению для разработки и эксплуатации систем персонализации, которые поддерживают обнаружение контента и вовлеченность пользователей.

Вы будете развивать модели рекомендаций, улучшать поиск и ранжирование, проводить эксперименты и A/B тестирование, использовать облачные платформы и контейнеры, работать в кросс-функциональной команде.

Formación

• 3+ years of experience applying ML methods, with focus on recommender systems, search, ranking, or personalization.
• Python proficiency for production ML systems.
• Experience with A/B testing and experimentation frameworks.
• Familiarity with AWS, GCP, or Azure and containerized environments.
• Familiarity with SQL and NoSQL databases.
• Degree in computer science, ML, statistics, or equivalent work experience.

Responsabilidades

• Design, build, and operate personalization systems powering content discovery and user engagement.
• Develop and improve ML models across the personalization stack from candidate generation to final ranking.
• Improve candidate retrieval using embeddings, two-tower architectures, and 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 in high-traffic environments.
• Collaborate with product managers, data scientists, and analysts to translate business needs into scalable solutions.

Descripción del empleo

Описание: Dow Jones is a global provider of news and business information, delivering content to consumers and organizations worldwide across print, digital, mobile, and live event formats.

Задачи

• Design, build, and operate personalization systems and services powering content discovery and user engagement;
• Develop and improve ML models across the personalization stack, from candidate generation to final ranking;
• Improve candidate retrieval using embeddings, two-tower architectures, and user and 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.

Требования

• 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 such as AWS, GCP, or Azure and containerized environments;
• Familiarity with SQL and NoSQL databases;
• Degree in computer science, machine learning, statistics, or equivalent work experience.

Условия

• Comprehensive healthcare plans for the employee and family, paid by Dow Jones;
• 30 Days of paid holidays per year;
• Remote work for 3 months per year through the desplazamiento program or one week of remote work per quarter;
• Meal benefit of 171€/month on top of salary;
• Retirement plan contributions: 2% of pensionable salary paid by Dow Jones and employee contribution matching up to 3%;
• Comprehensive insurance plans;
• Well-being resources, including a 200 USD quarterly allowance and ClassPass;
• Family care benefits and caregiving support;
• Subscription discounts;
• Employee referral program.