New York, NY
Los Angeles, CA
San Francisco, CA
Washington, District of Columbia, United States
- Bachelor's degree in Computer Science, a related field, or equivalent practical experience.
- 5 years of experience developing end-to-end production quality solutions with cloud computing.
- 3 years of experience in Machine Learning with focus on Deep Learning and developing NLP systems.
- Experience with the current state of AI/ML, Large Language Models, and Generative AI.
- Master's degree in Computer Science, Software Systems Engineering, or a related field.
- 5 years of experience working with enterprise and cloud technology systems, designing solutions, or developing business applications.
- Experience in one of the Large Language Model (LLM) frameworks such as T5X, PAX, Megatron-LM, etc.
- Experience in one of the deep learning frameworks such as JAX, PyTorch, or TensorFlow.
- Experience in machine learning engineering, including distributed training, large-scale serving, and machine learning accelerators.
The Google Cloud Platform team helps customers transform and build what's next for their business — all with technology built in the cloud. Our products are engineered for security, reliability and scalability, running the full stack from infrastructure to applications to devices and hardware. Our teams are dedicated to helping our customers — developers, small and large businesses, educational institutions and government agencies — see the benefits of our technology come to life. As part of an entrepreneurial team in this rapidly growing business, you will play a key role in understanding the needs of our customers and help shape the future of businesses of all sizes use technology to connect with customers, employees and partners.
As a Solution Architect with a core focus on Generative AI (GenAI), you will help customers discover use cases and better understand the potential GenAI. You scale your impact through publishing best practices, demos, tutorials, and developing code samples that customers can use to deploy. In this role, you will provide direction on how to tailor the mechanisms used to deploy workloads at scale reliably and securely to production, and apply Responsible AI principles. You will communicate with businesses of all types to help them adopt Google products and solutions wherever they are on their AI journey. You'll explore and experiment with our suite of products, partner tools, and third-party applications to build and deploy cloud 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 $167,000-$256,000 + 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.
- Facilitate technical discussions with customers, partners, and Googlers through all phases of customer engagements.
- Provide domain expertise around public cloud and enterprise technology, promote Google Cloud with customers, at conferences, and online.
- Create and deliver best practice recommendations, tutorials, blog posts, sample code, and presentations adapted to technical, business, and executive partners.
- Provide customer and market feedback to Product and Engineering teams to help define product direction.
- Work as part of a broader Solutions Go-To-Market team to contribute technical assets, prioritize, and shape solution direction, while impacting business and bookings.