Minimum qualifications:- Bachelor's degree in Engineering or equivalent practical experience
- 15 years of experience in ML infrastructure planning or deployment - in NPI or production
Preferred qualifications:- Master's degree in Engineering
- Solid understanding of infrastructure deployment processes, dependencies, constraints and acceleration approaches
About the jobWe seek a leader that will be responsible for driving execution of current ML infrastructure deployments and working closely with all partner teams involved.
In this key leadership role, you will be a key lead responsible for managing the execution and orchestration of ML infrastructure deployment for Google Product Areas and external customers. In addition, you'll be a key stakeholder in ensuring that our ML infrastructure planning is robust and comprehensive.
Individual pay is determined by factors including job-related skills, experience, and relevant education or training.
US: $281000 - $392000 (USD) 30% bonus target equity benefits
Learn more about benefits at Google .
Responsibilities- Work with planning leads to develop executable and deployment plans for Google's ML infrastructure. Ensure ML infrastructure plans make efficient use of power and cooling at a data center level.
- Drive execution of ML infrastructure deployments, ensuring timely delivery to meet Google's demand. Oversee execution escalations to ensure timely closure of issues and on-time delivery of capacity.
- Lead, mentor, and develop a high-performing team of execution leads for TPU/GPU platforms. Manage and allocate staff, budget, and resources effectively to achieve key objectives.
- Lead and influence cross-functional ML workstreams in a matrix environment to deliver outstanding acceleration outcomes.
- Work closely with leads in functional areas and data centers to drive scalable execution and acceleration at a multi-GW scale. Establish key performance indicators (KPIs) and metrics to monitor and improve the effectiveness of planning and execution.
