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Minimum qualifications:

+ Bachelor’s degree or equivalent practical experience.

+ 2 years of experience with software development in Python or C++ programming languages, or 1 year of experience with an advanced degree.

+ 1 year 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 a related machine learning field.

+ 1 year of experience with ML infrastructure (e.g., model deployment, model evaluation, optimization, data processing, debugging).

Preferred qualifications:

+ Master's degree or PhD in Computer Science, or a related technical field.

+ 2 years of experience with data structures or algorithms.

+ Experience developing accessible technologies.

+ Experience with Natural Language Processing (NLP) concepts or techniques.

+ Experience in statistics, databases, analytics, big data, or a related area.

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 Shopping Search Ads aims to make Google the best place for users' purchases, price-comparison, and shopping informational needs. Our team builds and deploys machine learning models to predict the relevance of shopping ads within Google.com search results, Google image search results, and in the Google shopping mode. These models are used in the retrieval phase where we first match products to users’ queries and tasks, and in the ads auction phase where we determine which ads are eligible to show, rank and price. The goal of this team is to improve the matches between users' queries and tasks and the product listing ads shown. We use state of the art machine learning techniques to predict human ratings of ads and incorporate those predictions into filtering and ranking.

In Google Search, we're reimagining what it means to search for information – any way and anywhere. To do that, we need to solve complex engineering challenges and expand our infrastructure, while maintaining a universally accessible and useful experience that people around the world rely on. In joining the Search team, you'll have an opportunity to make an impact on billions of people globally.

The US base salary range for this full-time position is $141,000-$202,000 + 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 (https://careers.google.com/benefits/) .

+ Write product or system development code.

+ Triage product or system issues and debug/track/resolve by analyzing the sources of issues and the impact on hardware, network, or service operations and quality.

+ Implement solutions in one or more specialized ML areas, utilize ML infrastructure, and contribute to model optimization and data processing.

+ Train machine learning models and explore model features, architectures, and hyperparameters in order to continuously improve model accuracy.

Google is proud to be an equal opportunity workplace and is an affirmative action employer. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or Veteran status. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. See also https://careers.google.com/eeo/ and https://careers.google.com/jobs/dist/legal/OFCCP_EEO_Post.pdf If you have a need that requires accommodation, please let us know by completing our Accommodations for Applicants form: https://goo.gl/forms/aBt6Pu71i1kzpLHe2.