Program Manager, Npi Technical Infrastructure Deployment Engineering

This role requires on-site presence at the contract manufacturer in Guadalajara three days per week.Note: Google’s hybrid workplace includes remote roles.**Remote location: Mexico.****Minimum qualifications**:- Bachelor's degree in a technical field or equivalent practical experience.- 2 years of experience in program or project management- Experience in NPI (new product introduction), data center operations or NPI deployment.**Preferred qualifications**:- Advanced degree in a technical field related to ML, Technical Infrastructure, Program Management, or equivalent professional experience.- Experience delivering executive briefings summarizing technical programs and their business impact.- Expertise in data analysis techniques, including the ability to manipulate, visualize, and interpret data to drive informed decision-making.- Expertise in computer/hardware engineering, machine learning deployments, networking, technology, large-scale infrastructure deployments, or data centers.- Proficiency in developing and utilizing automated dashboards to present data effectively, ensuring easy access to key metrics and program performance.**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 Machine Learning (ML) Supply Chain Operations team's mission is to deliver ML capacity predictably and at scale. We manage the planning and deployment process for ML hardware, both in the new product introduction phase and in production in Google's data centers. 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 Machine Learning products to the world.- In this role, you will lead deployment of new ML product introductions from concept to production. You will maximize the impact and efficiency of NPIs to data centers within the ML space. You'll navigate among highly interdependent and conflicting requirements and objectives across a wide range of cross-functional organizations, providing the judgment and leadership that results in optimal outcomes for Google and its users. You're comfortable explaining your team's analyses and recommendations to executives and discussing the technical trade-offs 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.**Responsibilities**:- Drive a set of cross-functional partners to develop and deliver ML deployment programs from inception to production.- Develop deployment schedules, documentation, process maps, presentations and tracking reports to provide detailed current status of each project.- Understand technical dependencies and considerations to drive project delivery, identify risks and create proposals for mitigation.- Ensure leaders and stakeholders are aware of progress/blockers on a continuous basis, drive strategic and tactical decisions throughout all organizations and levels.- Engage with cross-functional Subject Matter Experts (SMEs) and Team Leads (TLs) to streamline processes, simplify execution, manage Objectives and Key Results (OKRs), release on time, and improve tooling efficiency.Google is proud to be an equal opportunity workplace and is an affirmative action employer. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or Veteran status. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. See also Google's EEO Policy and EEO is the Law. If you have a disability or special need that requires accommodation, please let us know by completing our Accommodations for Applicants form.