Technical Program Manager III, AI/ML, Cloud AI Systems
Apply NowCompany: Google
Location: Austin, TX 78745
Description:
Minimum qualifications:
Preferred qualifications:
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 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.
As a Technical Program Manager for MSCA, you'll be instrumental in optimizing machine learning performance. You'll work closely with cross-functional partners to deliver groundbreaking ML/AI solutions, and play a pivotal role in shaping our technology roadmaps.
The ML, Systems, & Cloud AI (MSCA) organization at Google designs, implements, and manages the hardware, software, machine learning, and systems infrastructure for all Google services (Search, YouTube, etc.) and Google Cloud. Our end users are Googlers, Cloud customers and the billions of people who use Google services around the world.
We prioritize security, efficiency, and reliability across everything we do - from developing our latest TPUs to running a global network, while driving towards shaping the future of hyperscale computing. Our global impact spans software and hardware, including Google Cloud's Vertex AI, the leading AI platform for bringing Gemini models to enterprise customers.
The US base salary range for this full-time position is $156,000-$229,000 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
- Bachelor's degree in a technical field, or equivalent practical experience.
- 5 years of experience in program management.
- Experience managing machine learning or artificial intelligence programs.
Preferred qualifications:
- 5 years of experience managing cross-functional and/or cross-team projects.
- Experience with quantitative analysis, cost-effectiveness assessment techniques, and data quality metrics for AI products.
- Experience with machine learning algorithms and tools (e.g. TensorFlow), artificial intelligence, or deep learning.
- Experience in large-scale high performance serving systems.
- Experience in communicating technical concepts to non-technical audiences.
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 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.
As a Technical Program Manager for MSCA, you'll be instrumental in optimizing machine learning performance. You'll work closely with cross-functional partners to deliver groundbreaking ML/AI solutions, and play a pivotal role in shaping our technology roadmaps.
The ML, Systems, & Cloud AI (MSCA) organization at Google designs, implements, and manages the hardware, software, machine learning, and systems infrastructure for all Google services (Search, YouTube, etc.) and Google Cloud. Our end users are Googlers, Cloud customers and the billions of people who use Google services around the world.
We prioritize security, efficiency, and reliability across everything we do - from developing our latest TPUs to running a global network, while driving towards shaping the future of hyperscale computing. Our global impact spans software and hardware, including Google Cloud's Vertex AI, the leading AI platform for bringing Gemini models to enterprise customers.
The US base salary range for this full-time position is $156,000-$229,000 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
- Understand technical challenges from our users and work with the teams to prioritize and enable large-scale adoption.
- Prioritize program goals, understand and translate other stakeholders needs into program goals and prioritized deliverables with minimal assistance, and contribute to decisions on prioritizing goals and deliverables.
- Exercise independent judgment and develop recommendations that translate into a course of action.
- Deliver critical pieces of analysis and use these to drive new insights and uncover improvement opportunities, identifying and implementing large-scale measurable and scalable solutions for Machine learning projects.
- Build, maintain and enhance business, operational, and management dashboards.