Technical Program Manager III, Capacity Management, Cloud

A problem isn’t truly solved until it’s solved for all. That’s why Googlers build products that help create opportunities for everyone, whether down the street or across the globe. As a Technical Program Manager at Google, you’ll use your technical expertise to lead complex, multi-disciplinary projects from start to finish. You’ll work with stakeholders to plan requirements, identify risks, manage project schedules, and communicate clearly with cross-functional partners across the company. You're equally comfortable explaining your team's analyses and recommendations to executives as you are discussing the technical tradeoffs in product development with engineers.

Behind everything our users see online is the architecture built by the Technical Infrastructure team to keep it running. From developing and maintaining our data centers to building the next generation of Google platforms, we make Google's product portfolio possible. We're proud to be our engineers' engineers and love voiding warranties by taking things apart so we can rebuild them. We keep our networks up and running, ensuring our users have the best and fastest experience possible.

The US base salary range for this full-time position is $163,000-$237,000 + bonus + equity + benefits. Our salary ranges are determined by role, level, and location. 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

• Lead cross-functional programs related to ML Fleet capacity management, including the design, update, and maintenance of ML Fleet's cluster-level allocation plan of record.
• Drive the development, implementation, and ongoing maintenance of fleet-wide accelerator and auxiliary resource usage metrics, policies, and governance frameworks.
• Identify gaps and drive initiatives to improve existing tooling and processes, enhancing the efficiency, agility, and responsiveness of ML capacity allocation and management.
• Partner with key stakeholders including ML Strategy and Allocation (MLSA), Product Area Resource Management teams (PARMs), capital engineering, supply teams, tooling engineering (e.g., OneFleet, Tpulse, GQM Dev), and system infrastructure SREs (e.g., Spatial Flex, PIE).
• Manage communications and escalations related to ML resource allocation, performance, and strategic shifts for product areas and partners.

Minimum qualifications:

• Bachelor's degree in a technical field, or equivalent practical experience.
  
• 5 years of experience in program management.
• Experience with capacity management.
• Experience with data analytics and SQL.

Preferred qualifications:

• 5 years of experience managing cross-functional or cross-team projects.
• Experience with machine learning infrastructure.
• Experience with accelerators (e.g., TPUs/GPUs).

Note: By applying to this position you will have an opportunity to share your preferred working location from the following: Kirkland, WA, USA; Seattle, WA, USA; Sunnyvale, CA, USA.

In accordance with Washington state law, we are highlighting our comprehensive benefits package, which is available to all eligible US based employees. Benefits for this role include:

• Health, dental, vision, life, disability insurance
• Retirement Benefits: 401(k) with company match
• Paid Time Off: 20 days of vacation per year, accruing at a rate of 6.15 hours per pay period for the first five years of employment
• Sick Time: 40 hours/year (increased to 69 hours/year for Seattle) including 5 discretionary sick days per instance
• Maternity Leave (Short-Term Disability + Baby Bonding): 28-30 weeks
• Baby Bonding Leave: 18 weeks
• Holidays: 13 paid days per year