Software Engineering Manager, ML and GenAI, Ads Safety

Google's software engineers develop the next-generation technologies that change how billions of users connect, explore, and interact with information and one another. Our products need to handle information at massive scale, and extend well beyond web search. We're looking for engineers who bring fresh ideas from all areas, including information retrieval, distributed computing, large-scale system design, networking and data storage, security, artificial intelligence, natural language processing, UI design and mobile; the list goes on and is growing every day. As a software engineer, you will work on a specific project critical to Google’s needs with opportunities to switch teams and projects as you and our fast-paced business grow and evolve. We need our engineers to be versatile, display leadership qualities and be enthusiastic to take on new problems across the full-stack as we continue to push technology forward.

With your technical expertise you will manage project priorities, deadlines, and deliverables. You will design, develop, test, deploy, maintain, and enhance software solutions.

Google Ads is helping power the open internet with the best technology that connects and creates value for people, publishers, advertisers, and Google. We’re made up of multiple teams, building Google’s Advertising products including search, display, shopping, travel and video advertising, as well as analytics. Our teams create trusted experiences between people and businesses with useful ads. We help grow businesses of all sizes from small businesses, to large brands, to YouTube creators, with effective advertiser tools that deliver measurable results. We also enable Google to engage with customers at scale.Individual pay is determined by factors including job-related skills, experience, and relevant education or training.

US: $207000 - $301000 (USD) + 20% bonus target + equity + benefits

Learn more about benefits at Google.

• Manage a team of engineers who are focused on:
  enhancing and architecting the rollout of architecture across all new and refreshed workhorse models, solving the bottlenecks of traditional monolithic models and allowing parallel policy head updates.

Minimum qualifications:

• Bachelor’s degree or equivalent practical experience.
• 8 years of experience building AI-powered products, featuring technologies such as long context windows, Retrieval Augmented Generation (RAG), or similar.
• 2 years of experience in a people management, supervision/team leadership role.
• Experience building and architecting production quality Machine Learning (ML) systems.
• Experience building and deploying recommendation systems models (retrieval, prediction, ranking, personalization, search quality, embedding) in production.
• Experience building production quality ML systems.

Preferred qualifications:

• Experience in software engineering, applied ML, autonomous systems, and large-scale systems design.
• Experience in machine learning, large language model, large-scale data processing, project management, Generative AI Agent, thought leadership.
• Experience coordinating work between partners.
• Excellent cross-functional team collaboration skills.
• Proven track record in technical project management, with the ability to drive complex, multi-quarter ML initiatives to successful completion.