Senior Staff Software Engineer, Ads Content Safety AI/ML

About the role

MINIMUM QUALIFICATIONS:

• Bachelor’s degree or equivalent practical experience.

• 8 years of experience in software development.

• 7 years of experience leading technical project strategy, ML design and

optimizing end-to-end Machine Learning (e.g., model deployment, model

evaluation, data processing, debugging, fine tuning).

• 5 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.

• 5 years of experience with design and architecture; and testing/launching

software products.

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

and setting technical direction.

• 3 years of experience working in a complex, matrixed organization involving

cross-functional, or cross-business projects.

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.

The Ads Content Safety team are seeking an exceptional Senior Staff Software

Engineer whose defining characteristic is a relentless, adaptable

problem-solving mentality. In this role, you will operate as a technical leader

on Ad Safety, serving as the frontline operational and technical anchor for our

most critical challenges.

Whether the bottleneck is a complex machine learning limitation, a system-level

infrastructure failure, or a deep architectural flaw, you possess the attitude

and agility to drop into the context, untangle the ambiguity, and drive the

solution.

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: $262000 - $364000 (USD) + 25% bonus target + equity + benefits

Learn more about benefits at Google

[https://www.google.com/about/careers/applications/benefits/].

RESPONSIBILITIES:

• Design, develop, test, deploy, maintain, and enhance large scale software

solutions.

• Provide technical leadership on high-impact projects. Manage project

priorities, deadlines, and deliverables.

• Facilitate alignment and clarity across teams on goals, outcomes, and

timelines. Influence and coach a distributed team of engineers.

• Drive technical project strategy, lead large-scale ML infrastructure

optimization, and oversee the design and implementation of solutions across

multiple specialized ML areas.