Director, Engineering, AI Compute Infrastructure
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Minimum qualifications:
- Bachelor's degree in Computer Science, Electrical Engineering, or equivalent practical experience.
- 15 years of experience in software, hardware, or ML engineering, or in building distributed systems.
- 10 years of experience in team management/leadership, and managing geographically distributed teams.
- Experience in applied AI and building AI embedded systems and services.
- Experience in a general manager role, leading engineering and product teams.
Preferred qualifications:
- Master's degree or PhD in Computer Science, Electrical Engineering, or relevant field.
- Experience in building large-scale AI infrastructure supporting large-scale workloads.
- Experience working with Field Go-To-Market and Partner teams.
- Familiarity with AI developer frameworks and tools.
About the job
This team of AI experts collaborates closely with industry leaders, optimizing their machine learning workloads on GCP. They provide a premium experience, fine-tuning models for peak performance and efficiency. Beyond optimization, the team develops cutting-edge AI solutions and tools tailored to these large-scale customers.
The AI Ninja team also plays a crucial role in disseminating knowledge gained from these collaborations. They transform their expertise into accessible resources like solutions, code samples and best practices, empowering the broader AI community. This collaborative approach fuels GCP's AI Infrastructure growth and adoption.
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 $278,000-$399,000 + 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
- Acquire, retain, and grow AI Hyperscalers and large customers on Google Compute Engine's (GCE’s) accelerator products.
- Deliver customized and optimized AI models, solutions, code repos, and AI best practices to customers.
- Build and grow a senior AI Engineering team that is geographically distributed in North America, Europe, and Asia, to execute a multi-year strategy.
- Collaborate closely with cross-functional teams inside and outside of Google and influence their product roadmaps to ensure the timely delivery of new product initiatives to customers.
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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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