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.

Ads Artificial Intelligence (AI) is a unique team in Ads that applies Machine Learning (ML) and AI technology to solve issues in Ads, with a focus on Large Modeling (both Large Language Models and Large Embedding Models), Multimodal Generative Artificial Intelligence, and Agentic Reasoning.

In this role, you will work on applying AI techniques for solving critical problems in Search Ads Quality. You will design AI innovations to improve core Search Ads products, which has led to multiple high-impact launches. You will grow to do research on developing novel techniques and capabilities, which gets published in leading conferences.

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

• Work on problems in Ads, using the technologies that Ads AI is developing in partnership with Research teams.

• Solve problems and implement solutions that meet the quality and latency bar needed in Ads by partnering with teams in Ads and research.

• Use available tools, relying on everything from Agentic Artificial Intelligence and fine-tuning Large Language Models to improving Large Embedding Models through Large Language Models.

• Maintain interest in publishing, sharing insights, and building bridges with the academic community to share work with the rest of the AI community.

• Collaborate as a team of experts in multiple fields in AI and ML to solve problems in Ads.

Minimum qualifications

• Bachelor’s degree or equivalent practical experience.

• 8 years of experience programming in Python or C++.

• 5 years of experience leading ML design and optimizing ML infrastructure (e.g., model deployment, model evaluation, data processing, debugging, fine tuning).

• 5 years of experience testing, and launching software products.

• 3 years of experience with software design and architecture.

• 2 years of experience with GenAI techniques (e.g., LLMs, Multi-Modal, Large Vision Models) or with GenAI-related concepts (language modeling, computer vision).

Preferred qualifications

• Master’s degree or PhD in Engineering, Computer Science, or a related technical field.

• 8 years of experience with data structures and algorithms.

• 3 years of experience working in a matrixed organization involving cross-functional or cross-business projects.

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

• 2 years of experience leading a research agenda.

• Experience building or deploying AI platforms or Generative Artificial Intelligence Agents.