Please submit your resume in English - we can only consider applications submitted in this language.
Only applications of candidates with Mexican citizenship will be evaluated for this role in compliance with the provisions of Article 7 of the Federal Labor Law.
Note: Google's hybrid workplace includes remote roles.
Remote location: Mexico.
- Bachelor's degree or equivalent practical experience.
- 2 years of experience in program or project management.
- 2 years of experience managing programs and processes across distributed systems.
- Experience in program deployments or functional leadership roles, including experience at the subject matter expert level.
- Experience in data analysis techniques, with the ability to manipulate, visualize, and interpret data to drive informed decision-making.
- Experience in one or more relevant disciplines in computer/hardware engineering, machine learning deployments, networking, technology, or large-scale infrastructure deployments, supply chain or data center.
- Proficiency in developing and utilizing automated dashboards to present data effectively, ensuring easy access to key metrics and program performance.
- Ability to deliver executive briefings summarizing technical programs and their business impact.
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 Operations and Deployment Engineering (MODE) team's mission is to deliver ML capacity predictably and at scale. We do this through agile planning, deployment speed and efficiency, and enablement of partner teams. We manage the end-to-end planning and deployment process for ML hardware, both in the New Product Introduction phase and in production in Google's Data Centers.
Within MODE, The Technical infrastructure Deployment Engineering ML (TIDE-ML) team is responsible for orchestration of New Product Introduction (NPI) deployments, the required processes, policies, and infrastructure/networking dependencies to introduce our Machine Learning products that form the foundation of Google's AI efforts to the world.
- 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.
- Possess problem-solving, negotiation and organizational skills.
- Ensure leaders and stakeholders are aware of progress/blockers on a continuous basis; drive strategic and tactical decisions throughout all organizations and levels.
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.
