The Staff Software Engineer for YouTube ML Efficiency will focus on enhancing machine learning and AI workloads that power YouTube. This role involves working at the intersection of modeling and efficiency, particularly in evolving YouTube's models for next TPU generations. The engineer will be part of a team dedicated to improving performance and maximizing efficiency in recommendation systems. The position requires a blend of technical expertise and leadership to drive innovation in machine learning infrastructure.

• Bachelor’s degree or equivalent practical experience.
• 8 years of experience in software development.
• 5 years of experience leading ML design and optimizing ML infrastructure.
• 3 years of experience building large-scale recommendation systems, ML, ranking, or personalization.

• Monitor the evolving landscape of recommendation systems and prototype emerging modeling techniques.
• Enable next-generation model architectures and training procedures.
• Scale experimentation capacity under resource constraints.
• Reduce complexity and fragmentation in the ML training and serving ecosystem.
• Introduce automation frameworks for training, evaluation, and model serving.

• Employees at Google are often offered benefits like comprehensive health insurance, 401(k) matching, and flexible work arrangements, among other benefits.