Google
Machine Learning Engineer, Cloud Expansion, Retention
Google, Kirkland, Washington, United States, 98034
Machine Learning Engineer, Cloud Expansion, Retention
Location: Seattle, WA, USA; Kirkland, WA, USA
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.
5 years of experience with one or more of the following: Speech/audio, reinforcement learning, ML infrastructure, or another ML field.
5 years of experience with ML design and ML infrastructure (model deployment, model evaluation, data processing, debugging, fine‑tuning).
Experience in Python and ML libraries/frameworks.
Preferred Qualifications
Master’s degree or PhD in Engineering, Computer Science, or a related technical field.
8 years of experience with data structures/algorithms.
3 years of experience in a technical leadership role leading project teams and setting technical direction.
3 years of experience working in a structured organization involving cross‑functional or cross‑business projects.
Experience with data pipeline technologies.
Experience with cloud platforms (such as GCP).
About The Job Google's software engineers develop next‑generation technologies that change how billions of users connect, explore, and interact with information and one another. Our products handle information at massive scale and extend well beyond web search. We are looking for engineers who bring fresh ideas from all areas—including information retrieval, distributed computing, large‑scale system design, networking, data storage, security, artificial intelligence, natural language processing, UI design, and mobile—to help build and improve our products.
In this role you will design, build, and scale the machine learning systems that power Google Cloud Platform’s Product‑Led Sales Assist (PLSA) initiative. PLSA drives Cloud business growth by identifying high‑potential Product Qualified Leads (PQLs). You will manage the end‑to‑end ML lifecycle—from data pipelines and feature engineering to model development, deployment, and infrastructure management—collaborating closely with engineers, UX designers, product managers, analysts, and go‑to‑market teams. Your work will also extend to the suggestion platform where ML expertise improves ranking and audience targeting.
Google Cloud accelerates every organization’s ability to digitally transform its business and industry. Our solutions leverage cutting‑edge technology, and our tools help developers build more sustainably. Customers in more than 200 countries and territories rely on Google Cloud as their trusted partner.
Salary: US base range $197,000‑$291,000 + bonus + equity + benefits. Compensation details reflect the base salary only and do not include bonus, equity, or benefits.
Responsibilities
Design, build, and maintain scalable training, deployment, and monitoring infrastructure for machine learning models, including ML pipelines like XFlow.
Refine existing ML models and implement new models. Explore and implement integrations with Gemini to enhance PQL generation, signal reasoning, and insights.
Develop and manage data pipelines to ingest and process datasets (e.g., product data, Marketplace API data) for ML models. Drive feature extraction, manipulation, and exploration to create rich signals for PQLs across Google Cloud products.
Implement systems to monitor performance and health of ML pipelines and models, ensuring reliability, accuracy, and timely insights.
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. If you have a disability or special need that requires accommodation, please let us know by completing our Accommodations for Applicants form.
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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.
5 years of experience with one or more of the following: Speech/audio, reinforcement learning, ML infrastructure, or another ML field.
5 years of experience with ML design and ML infrastructure (model deployment, model evaluation, data processing, debugging, fine‑tuning).
Experience in Python and ML libraries/frameworks.
Preferred Qualifications
Master’s degree or PhD in Engineering, Computer Science, or a related technical field.
8 years of experience with data structures/algorithms.
3 years of experience in a technical leadership role leading project teams and setting technical direction.
3 years of experience working in a structured organization involving cross‑functional or cross‑business projects.
Experience with data pipeline technologies.
Experience with cloud platforms (such as GCP).
About The Job Google's software engineers develop next‑generation technologies that change how billions of users connect, explore, and interact with information and one another. Our products handle information at massive scale and extend well beyond web search. We are looking for engineers who bring fresh ideas from all areas—including information retrieval, distributed computing, large‑scale system design, networking, data storage, security, artificial intelligence, natural language processing, UI design, and mobile—to help build and improve our products.
In this role you will design, build, and scale the machine learning systems that power Google Cloud Platform’s Product‑Led Sales Assist (PLSA) initiative. PLSA drives Cloud business growth by identifying high‑potential Product Qualified Leads (PQLs). You will manage the end‑to‑end ML lifecycle—from data pipelines and feature engineering to model development, deployment, and infrastructure management—collaborating closely with engineers, UX designers, product managers, analysts, and go‑to‑market teams. Your work will also extend to the suggestion platform where ML expertise improves ranking and audience targeting.
Google Cloud accelerates every organization’s ability to digitally transform its business and industry. Our solutions leverage cutting‑edge technology, and our tools help developers build more sustainably. Customers in more than 200 countries and territories rely on Google Cloud as their trusted partner.
Salary: US base range $197,000‑$291,000 + bonus + equity + benefits. Compensation details reflect the base salary only and do not include bonus, equity, or benefits.
Responsibilities
Design, build, and maintain scalable training, deployment, and monitoring infrastructure for machine learning models, including ML pipelines like XFlow.
Refine existing ML models and implement new models. Explore and implement integrations with Gemini to enhance PQL generation, signal reasoning, and insights.
Develop and manage data pipelines to ingest and process datasets (e.g., product data, Marketplace API data) for ML models. Drive feature extraction, manipulation, and exploration to create rich signals for PQLs across Google Cloud products.
Implement systems to monitor performance and health of ML pipelines and models, ensuring reliability, accuracy, and timely insights.
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. If you have a disability or special need that requires accommodation, please let us know by completing our Accommodations for Applicants form.
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