yoinka

Staff ML Engineer, Search Ads Shopping Relevance Models

Google

Mountain View, CA, USAStaff$207k – $300k/yrH-1B sponsor company
Sign in to applyVerified 2h ago
Location
Mountain View, CA, USA
Work model
On-Site
Level
Staff
Salary
$207k – $300k/yr
H-1B history
2,460 approvals (FY2023)
Posted
2h ago

Skills

Deep LearningMachine LearningNLPPython

About this role

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. With your technical expertise you will manage project priorities, deadlines, and deliverables. You will design, develop, test, deploy, maintain, and enhance software solutions. Google Shopping Search Ads aims to make Google the best place for users’ purchases, price-comparison, and shopping informational needs. Our features and models impact the shopping commercial unit on google.com, often the top of the page for a shopping-related query. We also impact commercial units on image search, where users may have a more visual or in-depth shopping journey. Our mission is to improve the matches between users' queries and tasks and the product listing ads that we show. We use state of the art machine learning techniques to predict human ratings of ads and incorporate those predictions into filtering and ranking of ads. 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. Individual pay is determined by factors including job-related skills, experience, and relevant education or training. US: $207000 - $300000 (USD) + 20% bonus target + equity + benefits Learn more about benefits at Google .

Collaborate on user journey understanding, metric and label formulation, feature and model improvements, live traffic experiments, data analysis, tools and infrastructure, and more, to predict and improve user experience on search ads. Train machine learning models and explore model features, architectures, and hyperparameters in order to continuously improve model accuracy, in particular Gemini model(s). Own and lead efforts to push our modeling, data or serving to new dimensions. Implement code and tests for model training (Python, C++, e.g. on top of REX) and backend code and tests for model serving (in C++) and logging. Run ads experiments and develop experiment metrics, if needed. Interpret, understand, and integrate a wide variety of metrics related to user experience and quality. Perform model, experiment, and human evaluation analyses including writing custom analysis tools if needed.

Minimum qualifications: Bachelor’s degree or equivalent practical experience. 8 years of experience programming in Python or C++. 5 years of experience testing, and launching software products. 5 years of experience leading ML design and optimizing ML infrastructure (e.g., model deployment, model evaluation, data processing, debugging, fine tuning). 5 years of experience with one or more of the following: Speech/audio (e.g., technology duplicating and

Listing verified 2h ago. Applications go through the company's official careers site.

← Back to Yoinka

Staff ML Engineer, Search Ads Shopping Relevance Models at Google, Mountain View, CA, USA | Yoinka