Engineering Manager, Ads ML Modeling

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 in a people management or team leadership role. Experience working with SQL. 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 involving cross-functional, or cross-business projects. Experience in Ads. Experience in C++. Experience in Flume. Experience working with nonlinear regression modeling, classification, and time series regression. About the job Like Google's own ambitions, the work of a Software Engineer goes beyond just Search. Software Engineering Managers have not only the technical expertise to take on and provide technical leadership to major projects, but also manage a team of Engineers. You not only optimize your own code but make sure Engineers are able to optimize theirs. As a Software Engineering Manager you manage your project goals, contribute to product strategy and help develop your team. Teams work all across the company, in areas such as information retrieval, artificial intelligence, natural language processing, distributed computing, large-scale system design, networking, security, data compression, user interface design; the list goes on and is growing every day. Operating with scale and speed, our exceptional software engineers are just getting started -- and as a manager, you guide the way. With technical and leadership expertise, you manage engineers across multiple teams and locations, a large product budget and oversee the deployment of large-scale projects across multiple sites internationally. The Ads Optimization Quality ML Modeling Team builds and maintains models to improve the optimization of advertisers' campaigns and accounts. The team is highly innovative, product-focused and collaborative. It's an integral part of the broader Ads Optimization Quality team, and also works closely with various partner teams. The team has made critical contributions to multiple high-visibility, high-impact products, including forecasting traffic for new campaign creation, forecasting seasonal traffic changes, predictive caching to reduce initial page load latency in the Ads UI and UI ranking models to increase engagement with optimization features. 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. Responsibilities Manage and mentor engineer ML team, providing technical guidance, code reviews, and career development. Partner with leadership to set technical direction, align with product strategy, and drive quarterly planning and execution. Architect, prototype, and research new modeling applications, data analyses, and methodologies. Manage tactical coding, on-call escalations, and infrastructure support to keep the core team focused on main deliverables. Partner across the broader Ads Optimization organization to identify new opportunities and deliver platform services.