Location: Sunnyvale, CA
Company: Google
to data analysis and support, you will oversee the technical execution and business operations of Google's online advertising platforms and/or product partnerships. You will be able to balance business and partner needs with technical constraints, develop innovative, cutting edge solutions and act as a partner and consultant to those you are working with.
You will also be able to build tools and automate products, oversee the technical execution and business operations of Google's partnerships, as well as develop product strategy and prioritize projects and resources. As a Generative AI Field Solutions Architect, you will support Google Cloud sales and engineering teams to incubate, pilot,
and deploy Google Cloud's industry leading AI/ML and Generative AI technology with customers where we jointly build consumer products together. In this role, you will identify, backss and develop Generative AI and AI/ML applications by applying key industry tools, techniques, and methodologies to embed Google Cloud into the products and consumer surfaces that our customers build.
You will learn how Google designs the user experience of a consumer-facing product and guides customers through the use case selection. You will work closely with internal Cloud AI teams to remove roadblocks and shape the future of our offerings while navigating ambiguity, troubleshooting and finding solutions.
Google Cloud accelerates organizations' ability to digitally transform their business with the best infrastructure, platform, industry solutions and expertise.
We deliver enterprise-grade solutions that leverage Google's cutting-edge technology - all on the cleanest cloud in the industry. 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 $215,000-$315,000 bonus equity benefits. Our salary ranges are determined by role, level, and location. The range displayed on each job posting reflects the minimum and maximum target for new hire salaries for the position across all US locations.
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. Minimum qualifications: Bachelor's degree in Science, Technology, Engineering, Math, or equivalent practical experience.
7 years of experience in AI applications (e. g. deep learning, NLP, computer vision, or pattern recognition). Experience in statistical programming language (e. g. Python), applied machine learning techniques, and using OSS frameworks (e. g. Tensor Flow, Py Torch). Experience delivering technical presentations and leading business value sessions. Preferred qualifications: Master's degree in Computer Science, Engineering, or a related technical field. Experience designing and deploying with one or more from the following ML frameworks such as Tensor Flow, Py Torch, JAX, Spark ML.
Experience training and fine tuning models in large-scale environments (e. g. image, language, recommendation) with accelerators. Experience with CI/CD solutions in the context of MLOps and LLMOps including automation with Ia C (e. g. using terraform). Experience with distributed training and optimizing performance versus costs. Experience in systems design, with the ability to architect and explain data pipelines, ML pipelines, and ML training and serving approaches. Responsibilities Be a trusted advisor to the selected strategic customers, understand the customers business process and objectives related to creating consumer facing products.
Architect AI-drive, spanning Data, AI, and Infrastructure to include the full cloud stack into overall architecture. Demonstrate how Google Cloud is differentiated by working with customers demonstrating features, tuning models, optimizing model performance, profiling, etc. Troubleshoot and find solutions to issues training/serving models in a large-scale environment. Build repeatable technical assets such as scripts, reference architectures to enable other customers and internal teams.
Work cross-functionally to influence Google Cloud strategy and product direction at the intersection of infrastructure and AI/ML by advocating for enterprise customer requirements. Coordinate regional field enablement with leadership and work closely with product and partner organizations on external enablement activities. Travel as needed. Requisition #: 75143055121752774pca3lyuhf
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