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Google Looking for Enterprise Customer Engineer, AI Infrastructure, Google Cloud at Sunnyvale, CA, USA Full Time
Note: By applying to this position you will have an opportunity to share your preferred working location from the following: Sunnyvale, CA, USA; Atlanta, GA, USA; Austin, TX, USA; Chicago, IL, USA; New York, NY, USA.
Minimum qualifications:
- Bachelor’s degree in Computer Science, Mathematics, a related technical field, or equivalent practical experience
- 5 years of experience with cloud infrastructure
- Experience building and operationalizing machine learning models
- Experience in delivering technical presentations while leading detailed discovery and planning sessions that are aligned jointly with the customer with defined scope and success criteria
Preferred qualifications:
- Experience training and fine tuning large models (i.e., image, language, segmentation, recommendation, genomics) with accelerators
- Experience with running MLPerf benchmarks
- Experience with performance profiling tools (i.e., Tensorflow profiler, PyTorch profiler, Tensorboard)
- Experience with distributed training and optimizing performance versus costs
- Designing/architecting large scale infrastructure farms for specialist AI use cases
- Ability to engage with C-level or senior business leaders and influence decisions
About the job
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.
In this role, you will identify and assess large scale AI opportunities that would benefit from AI optimized infrastructure. You will help customers leverage accelerators within their overall cloud strategy by helping run benchmarks for existing models, finding opportunities to use accelerators for new models, developing migration paths, and helping to analyze cost to performance. Along the way, you would work closely with internal Cloud AI teams to remove roadblocks and shape the future offerings.
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 $130,000-$194,000 + 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.
Responsibilities
- Be a trusted advisor to our top customers, helping them understand and incorporate AI accelerators into their overall cloud strategy by recommending migration paths, integration strategies, and application architecture that incorporate Google Cloud AI optimized infrastructure
- Demonstrate how Google Cloud is differentiated, highlighting the power of accelerators by working with customers on POCs, demonstrating features, optimizing model performance, profiling, and bench-marking
- Build repeatable assets to enable other customers and internal teams
- Influence Google Cloud strategy at the intersection of infrastructure and AI/ML by advocating for enterprise customer requirements
- Travel to customer sites and events as needed