Senior Software Engineer, AI/ML, Ads Bidding

Google Inc.; New York (NY); On-site; USD 174,000 - 252,000; Full time

Job summary

Google Inc. is seeking a Senior Software Engineer, AI/ML, Ads Bidding in New York, NY.

You will design, implement, and deploy ML-powered ads bidding models that improve advertiser ROI and user experience across Search Ads. Join a collaborative team working on end-to-end ML model lifecycle—from training and evaluation to deployment at scale—using state-of-the-art AI techniques, including LLMs and large vision models.

Qualifications

• Bachelor's degree or equivalent practical experience.
• 5 years of experience programming in Python or C++.
• 3 years of experience testing, maintaining, or launching software products, and 1 year of experience with software design and architecture.
• 3 years of experience with end-to-end Machine Learning (e.g., model deployment, model evaluation, optimization, debugging).
• 3 years of experience with one or more of the following: LLMs, Multi-Modality, Large Vision Models, or reinforcement learning (e.g., sequential decision making).

Responsibilities

• Write and test product or system development code.
• 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).
• Contribute to existing documentation or educational content and adapt content based on product/program updates and user feedback.
• Solve complex machine learning related problems by designing, running, and analyzing experiments using analytical and statistical methods.
• Innovate and iterate on machine learning model design, improving quality, stability, and efficiency across the entire model life-cycle—from concept to deployment.

Skills

Python

C++

Testing & maintenance

ML lifecycle

LLMs & RL/vision

Education

Bachelor's degree or equivalent

Job description

Senior Software Engineer, AI/ML, Ads Bidding

Share Senior Software Engineer, AI/ML, Ads Bidding

corporate_fare Google place New York, NY, USA

• Bachelor’s degree or equivalent practical experience.
• 5 years of experience programming in Python or C++.
• 3 years of experience testing, maintaining, or launching software products, and 1 year of experience with software design and architecture.
• 3 years of experience with end-to-end Machine Learning (e.g., model deployment, model evaluation, optimization, debugging).
• 3 years of experience with one or more of the following: LLMs, Multi-Modality, Large Vision Models, or reinforcement learning (e.g., sequential decision making).

Preferred qualifications:

• Master's degree or PhD in a quantitative field such as Statistics, Engineering, or Mathematics.
• 5 years of experience with data structures/algorithms.
• 1 year of experience in a technical leadership role.

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.

We build and maintain machine learning models using state-of-the-art AI and ML techniques to predict user interactions on Search Ads. These models are a key component in setting advertisers' bids, with the goal of improving both satisfaction and return on investment for Search Ads advertisers using Auto-bidding products. By optimizing towards advertisers' objectives, Auto-bidding products drive Google's global Ads business.

You will be involved in the full machine learning model life-cycle, from design and training to deployment and serving models in production at the scale of billions of Search Ads. This role offers the opportunity to innovate while collaborating with other teams, including research teams, to test and implement the latest technologies in our models.

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.

We build and maintain machine learning models using state-of-the‑art AI and ML techniques to predict user interactions on Search Ads. These models are a key component in setting advertisers' bids, with the goal of improving both satisfaction and return on investment for Search Ads advertisers using Auto-bidding products. By optimizing towards advertisers' objectives, Auto-bidding products drive Google's global Ads business.

You will be involved in the full machine learning model life-cycle, from design and training to deployment and serving models in production at the scale of billions of Search Ads. This role offers the opportunity to innovate while collaborating with other teams, including research teams, to test and implement the latest technologies in our models.

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

• Write and test product or system development code.
• 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).
• Contribute to existing documentation or educational content and adapt content based on product/program updates and user feedback.
• Solve complex machine learning related problems by designing, running, and analyzing experiments using analytical and statistical methods.
• Innovate and iterate on machine learning model design, improving quality, stability, and efficiency across the entire model life‑cycle—from concept to deployment.

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.