Technical Program Manager III, ML Performance Optimization, Google Cloud

Minimum qualifications:

• Bachelor's degree in a technical field, or equivalent practical experience.
  
• 5 years of experience in program management.
  
• Experience working on hardware and performance (e.g., CPU/GPU).
  

Preferred qualifications:

• 5 years of experience managing cross-functional or cross-team projects.
  
• Experience in launching Machine Learning or Artificial Intelligence products from research to production.
  
• Ability to work independently in a fast paced environment, and work in the epicenter of teams of independent individuals.
• Excellent communication skills, with the ability to express ideas, follow up on tasks and questions on behalf of engineers, and communicate across a wide variety of functions, stakeholders, and levels.
  
• Excellent organizational and analytical skills, with the ability to think through design processes.

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.

Our goal is to build a Google that looks like the world around us — and we want Googlers to stay and grow when they join us. As part of our efforts to build a Google for everyone, we build diversity, equity, and inclusion into our work and we aim to cultivate a sense of belonging throughout the company.

As a Technical Program Manager, you will play a key role in improving Machine Learning performance. You will partner with product managers, engineers, and leadership to define roadmaps, prioritize features, and ensure timely releases.

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 $142,000-$211,000 + bonus + equity + benefits. Our salary ranges are determined by role, level, and location. The range displayed on each job posting reflects the minimum and maximum target salaries for the position across all US locations. 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

• Develop and manage the overall program for hardware performance improvements in pre-training, fine tuning and LLM serving areas including requirements gathering, risk assessment, and resource allocation.
  
• Work with researchers, engineers, and other stakeholders to define and prioritize features and capabilities across various work-streams.
  
• Track and manage the progress of various performance efforts identifying and mitigating risks, and ensuring that projects are completed on time and within budget.
  
• Communicate with stakeholders at all levels to keep them informed of the program's progress and to obtain their buy-in on key decisions.
  
• Support collaboration and coordination between the different teams involved in Machine Learning performance optimization.