Staff ML Software Engineering Manager, Google Display Ads

Responsibilities

• Define Technical Goal and Retrieval Architecture: Set the long-term roadmap and architect high-performance model architectures, embeddings, generative retrieval, and systems at scale.
• Drive AI Innovation: Pioneer the integration of cutting-edge AI and LLMs to deliver step-change improvements in relevance, model performance, and system efficiency.
• Optimize Infrastructure and Compute: Lead training and serving optimization strategies, maximizing TPU/GPU cluster utilization with high-performance production code (e.g., C++).
• Manage and Mentor Engineers: Lead and grow a high-performing team of ML and software engineers, providing technical guidance, driving execution, and elevating engineering excellence.
• Collaborate Across Functions: Partner cross-functionally with ML Research, Product Management, and Infrastructure teams to translate advanced concepts into impactful, production-ready systems.
• - Define Technical Goal and Retrieval Architecture: Set the long-term roadmap and architect high-performance model architectures, embeddings, generative retrieval, and systems at scale. - Drive AI Innovation: Pioneer the integration of cutting-edge AI and LLMs to deliver step-change improvements in relevance, model performance, and system efficiency. - Optimize Infrastructure and Compute: Lead training and serving optimization strategies, maximizing TPU/GPU cluster utilization with high-performance production code (e.g., C++). - Manage and Mentor Engineers: Lead and grow a high-performing team of ML and software engineers, providing technical guidance, driving execution, and elevating engineering excellence. - Collaborate Across Functions: Partner cross-functionally with ML Research, Product Management, and Infrastructure teams to translate advanced concepts into impactful, production-ready systems.

Minimum qualifications:

Preferred qualifications:

Qualifications

• Minimum qualifications: - 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 (e.g., model deployment, model evaluation, data processing, debugging, fine tuning). - 2 years of experience with state of the art GenAI techniques (e.g., LLMs, Multi-Modal, Large Vision Models) or with GenAI-related concepts (language modeling, computer vision). - 2 years of experience in a people management or team leadership role. - Experience in software engineering for recommendation systems or feed ranking architectures. Preferred qualifications: - Master’s degree or PhD in Engineering, Computer Science, or a related technical field. - 3 years of experience working in a complex, matrixed organization.