Program Manager III, NPI Deployment Engineering, Cloud Infrastructure
Job Description
- Bachelor's degree in technical field (ML, Infrastructure, Program Management)
- GPU and Data Center experience
- Experience in program deployments or functional leadership roles
- Expertise in computer/hardware engineering, ML deployments, networking, or large-scale infrastructure deployments
- 5+ years program/project management experience
- NPI, data center operations, or NPI deployment experience
- Cross-functional project management
- Lead ML product deployment from concept to production
- Develop deployment schedules and documentation
- Bonus
- Equity
- Benefits
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 deployment.
Preferred qualifications:
- Bachelor's degree in technical field related to ML, Infrastructure technical area, Program Management or equivalent experience.
- 5 years of experience managing cross-functional or cross-team projects.
- Experience with GPUs and Data Centers.
- Experience in program deployments or functional leadership roles, including experience at the subject matter expert level.
- Experience in one or more relevant disciplines in computer/hardware engineering, Machine Learning (ML) deployments, networking, technology, or large-scale infrastructure deployments, data center expertise, or experience.
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.
As the Program Manager, you will lead deployment of new ML 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 among conflicting requirements and objectives across a wide range of cross-functional organizations, and provide leadership that results in positive outcomes for Google and its users. You will be responsible for explaining the team's analyses and recommendations to executives as well as discussing the technical trade-offs in product development with design 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 $147,000-$216,000 + 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 .
Responsibilities
- Drive various sets of cross-functional partners to develop and deliver ML Deployment Programs from inception to production.
- Develop deployment schedules, documentation, process maps, presentations and track reports to provide detailed current status of each project.
- Set the outlook and direction for an ML NPI deployment program by outlining goals and objectives, evaluating and driving workstreams, organizing project work within the program, and defining program success criteria.
- 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.
