Manager, Software Engineering (AI/ML Platforms) at LinkedIn3

LinkedIn’s Trust organization is dedicated to maintaining a high standard for content on the platform. As part of this effort, the team develops and deploys machine learning models across diverse platforms, including Ads, feed, messaging, jobs, and more. The Content Abuse Prevention team focuses on enhancing the LinkedIn member experience by building scalable models that detect and prevent content abuse, particularly through advanced video-related initiatives. Leveraging large-scale video processing, video pipelines, multi-GPU optimization, and computer vision, we work to create robust solutions that identify and mitigate harmful video content. From idea conception and proof-of-concept to scalable design and framework development, your role will be vital in advancing our capabilities and ensuring a safer, more enriching digital community. At LinkedIn, our approach to flexible work is centered on trust and optimized for culture, connection, clarity, and the evolving needs of our business. The work location of this role is hybrid, meaning it will be performed both from home and from a LinkedIn office on select days, as determined by the business needs of the team. Responsibilities • Manage the performance and career development of a team of engineers, and own significant parts of LinkedIn products that require design, architecture, and coding. • Participate with senior management in developing a long-term technology roadmap. • Be a role model and professional coach for engineers with a strong bias for action and focus on craftsmanship. • Work with peers across teams to support and leverage a shared technical stack. • Manage teams to scale distributed applications, make architectural trade-offs applying synchronous and asynchronous design patterns, review code, and deliver with speediness and quality. • Develop multi-tier scalable, high-volume performing, and reliable user-centric applications that operate 24x7. • Produce high-quality software that is unit tested, code reviewed, and checked in regularly for continuous integration.