Machine Learning Engineer, Cloud Expansion, Retention
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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 (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.
- 5 years of experience with ML design and ML infrastructure (e.g., 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 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.
In this role, you will be designing, building, and scaling the machine learning systems that power our Product Led Sales Assist (PLSA) initiative. PLSA has significant impact in driving Google Cloud Platform (GCP) business growth expansion by identifying high-potential Product Qualified Leads (PQLs). You will be responsible for the end-to-end ML lifecycle, from data pipelines and feature engineering to model development, deployment, and infrastructure management. Your role will require an engineering background, machine learning (ML) expertise, and a passion for driving business impact through data. You will collaborate closely with other engineers, UX, PM, Analysts, and Go-to-Market teams and this can be expanded to the suggestion platform where ML expertise can be used to improve suggestion ranking and audience targeting.
Google Cloud accelerates every organization’s ability to digitally transform its business and industry. We deliver enterprise-grade solutions that leverage Google’s cutting-edge technology, and tools that help developers build more sustainably. Customers in more than 200 countries and territories turn to Google Cloud as their trusted partner to enable growth and solve their most critical business problems.
The US base salary range for this full-time position is $197,000-$291,000 + 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.
Responsibilities
- Design, build, and maintain the scalable infrastructure for training, deploying, and monitoring our machine learning models at scale, including leveraging ML pipelines like XFlow.
- Refine existing ML models and implement new models as needed. Explore and implement integrations with Gemini to enhance PQL generation, signal reasoning, and insights.
- Develop and manage data pipelines to ingest and process datasets (including product data, Marketplace API data) to feed into our ML models.
Drive feature extraction, manipulation, and exploration to create rich and potent signals for PQLs across a growing number of GCP products. - Implement systems to monitor the performance and health of ML pipelines and models, ensuring reliability, accuracy, and timely insights.
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Google is proud to be an equal opportunity and affirmative action employer. We are committed to building a workforce that is representative of the users we serve, creating a culture of belonging, and providing an equal employment opportunity regardless of race, creed, color, religion, gender, sexual orientation, gender identity/expression, national origin, disability, age, genetic information, veteran status, marital status, pregnancy or related condition (including breastfeeding), expecting or parents-to-be, criminal histories consistent with legal requirements, or any other basis protected by law. See also Google's EEO Policy, Know your rights: workplace discrimination is illegal, Belonging at Google, and How we hire.
If you have a need that requires accommodation, please let us know by completing our Accommodations for Applicants form.
Google is a global company and, in order to facilitate efficient collaboration and communication globally, English proficiency is a requirement for all roles unless stated otherwise in the job posting.
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