logo

Aprendizaje automático en Snap

Los ingenieros de aprendizaje automático de Snap trabajan de extremo a extremo y son dueños de todo el sistema de aprendizaje automático correspondiente.

Open Roles

Our engineers utilize state of the art models and continually push the boundaries of what’s possible in Snapchat's content, monetization, infrastructure, features, and more!

AI Lenses

Unified Recommendations

Dynamic Ads


Machine Learning Engineering at Snap

As a Machine Learning Engineer at Snap you’ll drive Snapchat’s dynamic experience through the full lifecycle of advanced state-of-the-art models -  from data preprocessing, feature engineering, and model training, to deployment and ongoing optimizations. You’ll leverage cutting-edge techniques, ranking algorithms for ad relevance, recommendation engines for personalized content and NLP for enhanced interactions - all while processing petabytes of data for over 850 million users. 

Through both classic and deep learning models, you’ll create precise, responsive experiences that empower users to express themselves, connect and discover the world in real-time.


“The real benefit that Snap has is the size of our scale, and the breadth of influence and impact that people will have. You can run fast, have broad influence and actually see your work hit production with the right experimentation tools and infrastructure to be productive.”

Equipos en aprendizaje automático

Our machine learning engineers solve real world ML problems.

Monetización

Como ingeniero de aprendizaje automático del equipo de monetización, construirás y optimizarás todo el ecosistema de anuncios. Impulsarás una alta relevancia y un alto impacto no solo para anunciantes y usuarios, sino para todo Snap. Desde el diseño de sistemas de alto rendimiento para pujas en tiempo real o servicio de anuncios y subastas, hasta la personalización de clasificadores ligeros y pesados, y la creación de soluciones para la segmentación y entrega de anuncios, seguirás garantizando una integración perfecta de los anuncios en toda la plataforma. Entrenarás modelos en miles de millones de ejemplos, usando aprendizaje multitarea, modelado de secuencias y modelado de interacción de usuario por anuncio. Nuestros modelos predicen los datos demográficos de usuario para mejorar la segmentación de la audiencia con redes neuronales y contenido de gráfico, para comprender cómo nuestro trabajo da forma al futuro de la plataforma publicitaria de Snapchat.

En qué trabajarás:

  • Publicidad impulsada por IA

  • Nuevos productos y experiencias de anuncio personalizados

  • Propietario del principal motor de ingresos de Snap

  • Desarrollo de productos de anuncio de vanguardia

Locations

Our RTO (Return to Office) policy is 4 times per week hiring in these office locations

Aprendizaje automático en Snap

Escucha al equipo sobre la vida en Snap en aprendizaje automático

We're Hiring!

Our interview process covers engineering, foundational, and applied ML.

Coding

Expect to solve algorithmic problems that test your proficiency in data structures, algorithms, and problem-solving skills. Focus on your ability to write clean, efficient, and well-documented code.

ML Fundamentals

You’ll be assessed on ML theory and core machine learning models, concepts, techniques and applications. Be prepared to discuss supervised and unsupervised learning, recommendation systems, ranking, model evaluation metrics, and optimization techniques.

ML Applied Design

Evaluates your ability to design and apply machine learning solutions to real-world problems. You may be asked to walk through the end-to-end process of selecting models, feature engineering, and evaluating performance. At times this can test your ability to problem solve in an ambiguous environment.

ML System Design

The focus will be on designing scalable and robust ML systems that can handle large-scale data and production environments. Expect to discuss the infrastructure and trade offs in architecture, model deployment strategies and system monitoring.

Our Interview Process