Lead Group Product Manager, Machine Learning, Silicon

Key Skills

Effective communication skills, Generative AI, JAX framework, Leadership, Machine learning techniques, Optimization, Product Management, PyTorch, SDLC, Software Development, TensorFlow

Job Description

Minimum qualifications:

• Bachelor's degree or equivalent practical experience.
• 10 years of experience in product management, consulting, co-founder or related technical role.
• 5 years of experience in people management, with technical leadership, and building and shipping technical products.
• Experience in ML optimizations on hardware accelerators or mobile ML software development.

Preferred qualifications:

• Master's degree or PhD in a relevant technical field.
• Experience defining and launching silicon products for consumer hardware.
• Experience working with cross-functional teams including research, silicon, software, system, operating systems, program management and product marketing teams.
• Familiarity with computing and software frameworks/tools and software development life cycles for ML solutions.
• Excellent communication skills to lead initiatives with key stakeholders and executive management.

About the job

At Google, we put our users first. The world is always changing, so we need Product Managers who are continuously adapting and excited to work on products that affect millions of people every day.

In this role, you will work cross-functionally to guide products from conception to launch by connecting the technical and business worlds. You can break down complex problems into steps that drive product development.

One of the many reasons Google consistently brings innovative, world-changing products to market is because of the collaborative work we do in Product Management. Our team works closely with creative engineers, designers, marketers, etc. to help design and develop technologies that improve access to the world's information. We're responsible for guiding products throughout the execution cycle, focusing specifically on analyzing, positioning, packaging, promoting, and tailoring our solutions to our users.

In this role, you will join the team that builds Google Tensor, Google’s custom System-on-Chip (SoC) that powers Pixel devices. You will help to productize the latest machine learning innovations and research by delivering state of the art heterogeneous computing hardware and software. You will drive the outlook for the Machine Learning Ecosystem of TensorFlow/JAX/PyTorch workflows, model repos, and first-party and third-party end-to-end developer journeys including ML and Generative AI.

Google's mission is to organize the world's information and make it universally accessible and useful. Our team combines the best of Google AI, Software, and Hardware to create radically helpful experiences. We research, design, and develop new technologies and hardware to make computing faster, seamless, and more powerful. We aim to make people's lives better through technology.

The US base salary range for this full-time position is $208,000-$306,000 + 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 for new hire 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. 

• Drive Tensor Processing Unit (TPU) roadmap for power, performance and area leadership, heterogenous performance for workload interactions with the rest of the system and memory subsystem.
• Work cross-functionally to prefetch research learnings through custom silicon and build multi-year roadmaps across Pixel features and secure executive support for the new initiatives. 
• Ensure on-device ML has a clear path to productization, and drive internal stakeholder and partner engagements necessary for the on-time launch of the product features.
• Define and lead workstreams to make the Tensor ML platform the clear choice for innovation and on-device deployment.
• Define differentiated and compelling Generative AI Silicon solutions and roadmap that leverage Google’s hardware, software, research and ML capabilities.