Description

Minimum qualifications:

• Bachelor's degree or equivalent practical experience.
  
• 5 years of experience in program or project management.
• Experience in new product introduction (NPI), data center operations, or NPI deployments.
• Experience in deployment planning.

Preferred qualifications:

• Bachelor's degree in technical field related to ML, Infrastructure technical area, Program Management or equivalent professional experience.
  
• 5 years of experience managing cross-functional or cross-team projects.
  
• Experience with GPUs.
• Expertise in one or more relevant disciplines in computer/hardware engineering, machine learning deployments, networking, technology, infrastructure deployments, or data center.
• Excellent aptitude for quantitative assessment and analysis across multiple technical disciplines.
• Ability to deliver executive briefings summarizing technical programs and their business impact.

About the job
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 Program Manager at Google, you'll lead complex, multi-disciplinary projects from start to finish - working with stakeholders to plan requirements, manage project schedules, identify risks, and communicate clearly with cross-functional partners across the company. Your projects will often span offices, time zones, and hemispheres. It's your job to coordinate the players and keep them up to date on progress and deadlines.

The Technical infrastructure Deployment Engineering ML (TIDE-ML) team is responsible for orchestration of NPI deployments and the required processes, policies, and infrastructure/networking dependencies to introduce our cutting-edge Machine Learning products to the world!

The TIDE-ML team leads and manages the end-to-end deployment for ML New Products Introduction. We orchestrate and coordinate the many cross-functional teams to ensure a smooth transition of NPI to Data Center (DC) deployment and ramp to Georgia (GA).

In this role, you will lead deployment of new product introductions from concept to production. You will maximize the impact and efficiency of new product introductions to the data centers within the ML space. Navigate amongst interdependent and conflicting requirements and objectives across a range of cross-functional organizations, providing the judgment and leadership that results in optimal outcomes for Google and its users. You are equally comfortable explaining your team's analyses and recommendations to executives as you are discussing the technical trade-offs in product development with engineers. You will also have experience with Graphics Processing Unit (GPU) products.

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 $159,000-$231,000 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

• Drive a set of cross-functional partners to develop and deliver ML Deployment Programs from inception to production.
• Develop deployment schedules, dependency mapping, deployment workflows, presentations and tracking reports to provide detailed current status of each project. Set the goal and direction for an ML NPI deployment program by outlining goals and objectives, evaluating and managing workstreams, organizing project work within the program, and defining program success criteria.
• Set ML NPI Product Deployment and Transition Strategy with required entry criteria for a successful delivery to downstream sustaining teams.
• Understand technical dependencies and considerations to drive project delivery, identify risks and create proposals for mitigation.

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Requisition #: 116905437948715718

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