ML Engineer, Search Ads Shopping Relevance Models

Staff ML Engineer, Search Ads Shopping Relevance Models

Location:

Mountain View, CA, USA

Experience Level: Advanced

Experience owning outcomes and decision making, solving ambiguous problems and influencing stakeholders; deep expertise in domain.

• 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 responding to the human voice), reinforcement learning (e.g., sequential decision making), ML infrastructure, or specialization in another ML field.
• 3 years of experience with software design and architecture.

• Master's degree or PhD in Engineering, Computer Science, or a related technical field.
• 8 years of experience with data structures and algorithms.
• 3 years of experience in a technical leadership role leading project teams and setting technical direction.
• 3 years of experience working in an organization involving cross-functional, or cross-business projects.
• Knowledge of modern machine learning techniques including deep learning and LLMs.
• Knowledge of statistics and experiment design.

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 , 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 You Tube 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: $207,000 - $300,000 (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…