Senior Software Engineer - Multiple Teams

• Set the technical direction for the team by collaborating with cross-functional partners and peer teams.
• Boost Google Ads sellers' productivity and impact through GenAI solutions.
• Work within changing, cross-functional teams to deliver engineering results.
• Design and implement solutions in one or more specialized ML areas, leverage ML infrastructure, and demonstrate expertise in a chosen field.
• Collaborate with peers and stakeholders through design and code reviews to ensure best practices amongst available technologies (e.g., style guidelines, checking code in, accuracy, testability, and efficiency.).

Minimum qualifications:

• Bachelor’s degree or equivalent practical experience.
• 5 years of experience with software development in one or more programming languages.
• 3 years of experience with end-to-end machine learning (e.g., model deployment, model evaluation, data processing, debugging).
• 3 years of experience with one or more of the following: speech/audio (e.g., technology duplicating and responding to the human voice), reinforcement learning (e.g., sequential decision making), ML infrastructure, or specialization in another ML field.
• Experience utilizing Agentic AI frameworks or developer kits to build and deploy autonomous AI systems.
• Experience working with Generative AI technologies (e.g., leveraging Large Language Models (LLMs) in application development).

Preferred qualifications:

• Experience applying generative artificial intelligence in production applications and solving real-world problems.
• Experience with Google Ads systems.
• Experience with the full life cycle of software and artificial intelligence application development.
• Experience making data-driven decisions to solve technical problems.
• Ability to guide teams to iterate quickly through changing technologies and user expectations.
• Ability to adapt to changes and make decisions to drive progress.

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 at the forefront of AI innovation, applying cutting-edge machine learning and Generative AI models like Gemini to power a multi-billion dollar global business.

Our work directly impacts billions of users by protecting users from harm, improving ad quality, and optimizing campaigns for advertiser return-on-investment. We foster a culture of deep collaboration, partnering closely with teams like Google Research and DeepMind to solve complex challenges. Join us to work on state-of-the-art AI, take on problems at an unparalleled scale, and build the next generation of advertising technology.

Individual pay is determined by factors including job-related skills, experience, and relevant education or training.

US: $174000 - $252000 (USD) + 15% bonus target + equity + benefits

Learn more about benefits at Google.

• Bachelor’s degree or equivalent practical experience.
• 5 years of experience with software development in one or more programming languages.
• 3 years of experience with end-to-end machine learning (e.g., model deployment, model evaluation, data processing, debugging).
• 3 years of experience with one or more of the following: speech/audio (e.g., technology duplicating and responding to the human voice), reinforcement learning (e.g., sequential decision making), ML infrastructure, or specialization in another ML field.
• Experience utilizing Agentic AI frameworks or developer kits to build and deploy autonomous AI systems.
• Experience working with Generative AI technologies (e.g., leveraging Large Language Models (LLMs) in application development).