Machine Learning Manager (Feed Relevance, Retrieval)

Join Reddit as a Machine Learning Manager to lead the Feed Retrieval team. In this high-impact role, you will define the technical vision and long-term roadmap for Feed Retrieval, oversee the design and development of retrieval systems, and collaborate with cross-functional partners. You will also coach and support the development of your team, establish strong measurement and experimentation practices, and maintain high standards for system performance and reliability.

• Definir la visión técnica y la estrategia a largo plazo para la Recuperación de Feed, alineando las inversiones en sistemas de recomendación a gran escala con los objetivos de producto y negocio de Reddit.
• Traducir los amplios objetivos de Relevancia de Feed en una hoja de ruta enfocada para el equipo, haciendo claras las compensaciones de priorización en calidad del modelo, expansión de inventario, velocidad de experimentación, costo de infraestructura y fiabilidad operativa.
• Supervisar el diseño, desarrollo y optimización de los sistemas de recuperación que obtienen candidatos relevantes, diversos, frescos y de alta calidad para experiencias de feed personalizadas.
• Impact-Driven Mindset: Passion for developing scalable, well-designed, and responsible AI solutions that drive business value
• Experience Leading ML Teams: 2+ years of experience building and managing high-performing ML or recommender-systems teams
• Strategic Thinking: Ability to develop and communicate a clear technical strategy across ambiguous problem spaces, balancing user relevance, ecosystem health, system scalability, and business impact
• Technical Domain Knowledge: Strong understanding of recommender systems, especially candidate retrieval, embedding/indexing systems, ranking handoffs, feed personalization, exploration, content quality, and measurement strategies
• Exceptional Communication & Collaboration: Strong interpersonal skills and a collaborative mindset, with the ability to effectively communicate complex technical topics to diverse audiences and build strong relationships with cross-functional partners
• Deep ML Expertise: Hands-on experience with large-scale production ML systems, ideally including recommender systems, retrieval models, embedding-based systems, sequence models, transformer-based architectures, or LLM-powered recommendation applications