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Staff ML Engineer, Search Ads Auto-Bidding

$207k - $300k

Google

Innovate and iterate on machine learning model design to improve quality, stability, and efficiency across the entire model lifecycle from concept to deployment.Solve complex machine learning problems by designing, running, and analyzing experiments using analytical and statistical methods.Contribute to code health, automation, and alerting systems to ensure model stability and performance.Participate in on-call rotations for model health and collaborate with team members to support critical systems.Minimum qualifications:Bachelor’s degree or equivalent practical experience.8 years of experience in software development.5 years of experience testing, and launching software products, and 3 years of experience with software design and architecture.Experience with deep learning, transformers, or large language models (LLMs).Experience with machine learning model training and inference performance, and programming in Python or C++.Preferred qualifications:Master’s degree or PhD in Engineering, Computer Science, or a related technical field.Experience designing and analyzing experiments for machine learning models.Experience with machine learning frameworks and libraries (e.g., TensorFlow, Keras, or TFX).Experience deploying and maintaining machine learning systems in production environments.Experience working with advertising systems or related technologies.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 Search Ads Auto-Bidding team builds and maintains machine learning models using 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 ROI for Search Ads advertisers using auto-bidding products. By optimizing towards advertisers' objectives, auto-bidding products drive Google's global Ads business, which serves users and generates business growth.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 + benefitsLearn more about benefits at Google.Bachelor’s degree or equivalent practical experience.8 years of experience in software development.5 years of experience testing, and launching software products, and 3 years of experience with software design and architecture.Experience with deep learning, transformers, or large language models (LLMs).Experience with machine learning model training and inference performance, and programming in Python or C++.

Vacancy posted 7 days ago
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