Description

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.
• 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.
• 2 years of experience in a people management, supervision/team leadership role.

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.
• Strong cross-functional team collaboration skills and experience coordinating work between partners.
• Proven track record in technical project management, with the ability to drive complex, multi-quarter ML initiatives to successful completion.

About the job
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.

Our mission is to accelerate ML innovation and revolutionize ad policy enforcement through a scalable, automated platform.

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.

The US base salary range for this full-time position is $207,000-$300,000 bonus equity benefits. Our salary ranges are determined by role, level, and location. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training. Your recruiter can share more about the specific salary range for your preferred location during the hiring process.

Please note that the compensation details listed in US role postings reflect the base salary only, and do not include bonus, equity, or benefits. Learn more about benefits at Google.

Responsibilities

• 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 independent, parallel policy head updates.
• Drive the migration of LLM Boosters to the low-latency serving platform to dramatically reduce the time harmful ads are live (from >24 hours to ~15 minutes or real time).
• Lead our agentic solutions toolkit to automate the model training lifecycle, utilizing AI agents to evaluate models and optimize prompts to completely remove human raters from the critical path.
• Support the transition from complex, multi-layered FLAMeD fine-tuning to In-Context Learning (ICL) on Base Gemini models.
• Scale state-of-the-art agile response platforms to onboard the next wave of high-risk policies.

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Requisition #: 85611833246786246

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