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X Note: By applying to this position you will have an opportunity to share your preferred working location from the following:
Sunnyvale, CA, USA; Austin, TX, USA; Redwood City, CA, USA.
Minimum qualifications: - Bachelor's degree in Electrical or Computer Engineering, a related field, or equivalent practical experience.
- 15 years of relevant technical program management or supply chain management experience in Technology, Chip Manufacturing, or a related industry.
- Experience with the domain area of NPI launch, Hardware Manufacturing, Supply Chain operations, and Technical Operations.
- Experience working with technical commodities (e.g., silicon, memory, optics, storage, networking).
Preferred qualifications: - Master's degree in Electrical Engineering or MBA.
- Exceptional executive presence with expert S/VP-level communication and influence skills.
- Deep technical expertise in systems and software with leadership skills to influence technical leaders across the company.
About the jobAs the Senior Director, Product Verticals (ML), you will lead a critical NPI-focused function aligned specifically to Google's Machine Learning product portfolio. This pivotal leadership role is designed to look across commodities-including silicon, memory, and optics-to ensure disjointed strategies come together into cohesive, executable integrated program plans.
You will manage a multi-disciplinary organization comprising Operations Program Managers (Ops PMs), Supply Chain Program Managers (SCPMs), and Product Manufacturing Engineers (PMEs) across both NPI and sustaining phases. Reporting into the ISM leadership, you will partner closely with executives across Cloud and Google, to ensure our supply chain and operational readiness align with the overall ML/AI product roadmap.
Individual pay is determined by factors including job-related skills, experience, and relevant education or training.
US: $336000 - $467000 (USD) 40% bonus target equity benefits
Learn more about benefits at Google .
Responsibilities - Drive the planning, execution, and delivery of complex supply chain programs for ML products, from NPI to end-of-life (EOL). Ensure the successful launch of time-sensitive products into deployment to support growing AI infrastructure needs.
- Lead and inspire an organization of Ops PMs, SCPMs, and PMEs. Build a healthy, scalable, and growth-oriented organization across multiple locations, managing resourcing requirements while driving sublinear scaling at a rapid pace.
- Enable the tools, processes, and OKRs required to scale effectively. Look across individual commodity silos to manage holistic product "square sets" and translate dependencies into unified roadmaps.
- Drive AI/ML adoption within supply chain operations and implement new methodologies to improve the efficiency of program management across the organization. Identify trends and resolve systemic problems across engineering organizations.
