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.

Discover is a proactive, recommendation-driven surface. We innovate on the Machine Learning (ML) models and applicant generation strategies that filter millions of potential ads down to a high-quality subset. Our work directly determines the upper bound of the entire ads system’s performance.

In this role, you will lead the retrieval strategy that connects users with the most relevant ads in their discover feed, a primary driver of Google’s social ads effort. You will retrieve high-quality relevant ads that provide real value to a user.

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 $262,000-$365,000 + 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

• Be the primary technical authority for our retrieval stack and move beyond incremental tuning to drive step-functions in ad relevance and quality. Lead a team of ML engineers to explore the frontiers of embedding-based retrieval, deep learning architectures, and multi-objective optimization (user value vs. advertiser success).

• Define the roadmap for retrieval quality. This includes moving from legacy retrieval methods (e.g., two-tower models, transformer-based embeddings, and generative retrieval).

• Innovate on how we measure and improve relevance. Lead efforts to align retrieval outputs with long-term user satisfaction and advertiser Return on Investment (ROI) ensuring we aren't just retrieving clicks, but value.

• Design next-generation applicant generation strategies. Oversee the integration of fresh signals (user intent, content semantics, and social trends) into our retrieval models to capture the dynamic nature of the discover feed.

Minimum qualifications

• Bachelor’s degree or equivalent practical experience.

• 8 years of experience with software development in one or more programming languages.

• 7 years of experience testing, maintaining or launching software products, and 1 year of experience with software design and architecture.

• 7 years of experience with AI/ML algorithms and tools, deep learning and AI/ML modeling.

• Experience building and deploying recommendation systems models (e.g., retrieval, prediction, ranking, personalization, search quality, embedding) in production.

Preferred qualifications

• Master degree or PhD in Computer Science, or a related field.

• 8 years of experience with data structures and algorithms and large language model applications.

• 5 years of experience in a technical leadership role leading project teams and setting technical direction.

• Experience developing algorithms (e.g., ranking, recommendations, prediction, search quality, personalization) and software that generates suggestions based on various input and output goals.

• Experience in quality working on content recommendation or user personalization problems.

• Experience in successfully applying machine learning approaches to real-world content problems, and excellent programming skills in Python.