Software Engineer III, AI/ML, Search Ads Bidding

Software Engineer III, AI/ML, Search Ads Bidding

Share Software Engineer III, AI/ML, Search Ads Bidding

corporate_fare Google place Mountain View, CA, USA

X In most instances, this position requires in-person interviews as part of the hiring process.

• Bachelor’s degree or equivalent practical experience.
  
• 2 years of experience with software development in Python or C++ .
• 2 years of experience applying mathematical modeling, numerical analysis, or statistical methods to solve engineering or scientific problems.
• 1 year of experience building and deploying recommendation systems models (retrieval, prediction, ranking, personalization, search quality, embedding) in production.
• 1 year of experience with end to end machine learning (e.g., model deployment, model evaluation, optimization, data processing, debugging).

Preferred qualifications:

• Master's degree or PhD in Computer Science or related technical fields.
• Experience with machine learning, statistical analysis, applied math, or operation research in the industry or in the academic sector.
• Experience productionizing machine learning systems or designing experiments.
• Experience with Google Ads systems or specialized ML tools such as TensorFlow, Keras, or TFX.
• Ability to to write high quality and low latency code/models that can train on and serve on every query.

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.

Google’s machine learning models drive the global Ads business, serving billions of users and generating significant business.

As a Software Engineer on the Proxybidder ML team, you will be involved in the full machine learning model lifecycle - from design and training to deployment and serving in production at the scale of billions of Search Ads. We are the team specializing in AI and ML for Search Ads bidding. Our mission is to build and deploy the large-scale Machine Learning models that predict user value, empowering advertisers to achieve peak return on investment (ROI) and driving a vital component of Google's business.

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.

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.

Google’s machine learning models drive the global Ads business, serving billions of users and generating significant business.

As a Software Engineer on the Proxybidder ML team, you will be involved in the full machine learning model lifecycle - from design and training to deployment and serving in production at the scale of billions of Search Ads. We are the team specializing in AI and ML for Search Ads bidding. Our mission is to build and deploy the large-scale Machine Learning models that predict user value, empowering advertisers to achieve peak return on investment (ROI) and driving a vital component of Google's business.

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: $147000 - $210000 (USD) + 15% bonus target + equity + benefits
Learn more about benefits at Google .

• Developand maintain machine learning models using advanced AI techniques to predict user interactions and optimize advertiser return on investment (ROI).
• Innovateon machine learning model design to improve quality, stability, and efficiency throughout the entire model lifecycle.
• Analyzeexperiments using statistical methods to solve complex machine learning problems and improve model generalization.
• Enhancemodel health and stability by contributing to code health, automation, and alerting systems.
• Collaboratewith Research and Infrastructure teams to test and implement the latest technologies in production environments.

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.

Equity is granted exclusively and discretionarily by Alphabet Inc. on the basis of an agreement concluded between you and Alphabet Inc. Alphabet Inc. is your sole contractual partner with respect to equity grants. GSU grants are not guaranteed, are discretionary, are subject to approval by the Alphabet Inc. board of directors or its delegate, the terms of the relevant Alphabet Inc. stock plan, and your grant agreement. They have no impact on statutory payments. Current or past grants do not confer an acquired right.

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