Software Engineer III, AI​/ML, Search Ads Quality

Software Engineer III, AI/ML, Search Ads Quality

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• Bachelor’s degree or equivalent practical experience.
• 2 years of experience with software development in one or more programming languages, or 1 year of experience with an advanced degree.
• 1 year of experience with one or more of the following: speech/audio, reinforcement learning, ML infrastructure, or specialization in another ML field.
• 1 year of experience with ML infrastructure (model deployment, model evaluation, optimization, data processing, debugging).

• Master's degree or PhD in Computer Science or related technical field.
• 2 years of experience with data structures and algorithms.
• Experience with Google's ML stack:
  Tensorflow, SAX, GeMax, TPUs, etc.
• End-to-end experience launching applied ML, NLP, or LLM projects.

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 manage information at a 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.

• Implement solutions in one or more specialized ML areas; utilize ML infrastructure; and contribute to model training optimization, and data processing.
• Write related product or system development code.
• Innovate and iterate on machine learning model training recipes, improving quality and efficiency across the entire model lifecycle.
• Test ML solutions by running and analyzing experiments using analytical and statistical methods.
• Collaborate with peers and stakeholders through design and code reviews to ensure best practices amongst available technologies (e.g., prompt optimization and training recipes, accuracy, testability, and efficiency).

Google is proud to be an equal opportunity and affirmative action employer. We are committed to building a workforce that is representative of the users we serve, creating a culture of belonging, and providing an equal employment opportunity regardless of race, creed, color, religion, gender, sexual orientation, gender identity/expression, national origin, disability, age, genetic information, veteran status, marital status, pregnancy or related condition (including breastfeeding), expecting or parents‑to‑be, criminal histories consistent with legal requirements, or any other basis protected by law.

See also Google’s EEO Policy , Know your rights: workplace discrimination is illegal , Belonging at Google , and How we hire .

Google is a global company and, in order to facilitate efficient collaboration and communication globally, English proficiency is a requirement for all roles unless stated otherwise in the job posting.

To all recruitment agencies:
Google does not accept agency resumes. Please do not forward resumes to our jobs alias, Google employees, or any other organization location. Google is not responsible for any fees related to unsolicited resumes.