Note: By applying to this position you will have an opportunity to share your preferred working location from the following: New York, NY, USA; Mountain View, CA, USA.

Minimum qualifications:

Bachelor’s degree or equivalent practical experience.
5 years of experience with software development in C++ or Python.
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 one or more of the following: sequence modeling, deep learning, natural language processing (NLP), reinforcement learning, or building machine learning models in production.

Preferred qualifications:

Master's degree or PhD in Computer Science, Mathematics, or a related science or technical field.
5 years of experience with data structures and algorithms.
1 year of experience in a technical leadership role.
Experience with ads bidding, mathematical optimization, or feedback loops.

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 Proxybidder team’s mission is to build exceptional bidding modeling, optimization algorithms and platforms for 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).

In this role, you will be at the center of the full machine learning life-cycle for Google's Search Ads bidding models. You will design, train, deploy, and serve models that operate at a massive scale, directly impacting billions of ads on Google Search. You will have the opportunity to innovate and collaborate with research teams to implement technologies.Google Ads is helping power the open internet with the best technology that connects and creates value for people, publishers, advertisers, and Google. We’re made up of multiple teams, building Google’s Advertising products including search, display, shopping, travel and video advertising, as well as analytics. Our teams create trusted experiences between people and businesses with useful ads. We help grow businesses of all sizes from small businesses, to large brands, to YouTube creators, with effective advertiser tools that deliver measurable results. We also enable Google to engage with customers at scale.

The US base salary range for this full-time position is $174,000-$252,000 + bonus + equity + benefits. Our salary ranges are determined by role, level, and location. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training. Your recruiter can share more about the specific salary range for your preferred location during the hiring process.

Please note that the compensation details listed in US role postings reflect the base salary only, and do not include bonus, equity, or benefits. Learn more about benefits at Google.

Responsibilities

Write and test product or system development code.
Develop and optimize bidding models to enhance and simplify the machine learning models.
Innovate the Model Life-cycle to drive improvements in quality, stability, and efficiency across all stages of model development, from initial concept to global deployment.
Design and execute advanced experiments using sophisticated investigative and statistical methods to solve complex machine learning challenges.
Enhance code health, develop automation processes, and refine alerting systems to guarantee model stability and peak performance.

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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.

If you have a need that requires accommodation, please let us know by completing our Accommodations for Applicants form.

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.

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