Senior Product Manager, Machine Learning Frameworks, Google Cloud

Minimum qualifications:

• Bachelor's degree or equivalent practical experience.
• 8 years of experience in product management, consulting, co-founder or related technical role.
• 3 years of experience building and shipping technical products.

Preferred qualifications:

• Experience with AI/ML model or tooling development (e.g., Product Management or Engineering).
• Experience with engineering in AI/ML development.
• Experience building developer tools (e.g., ML development).
• Experience with influencing cross-functional decisions involving participating stakeholders.

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.

The Core Machine Learning team builds the tooling, service, and technical foundations to enable machine learning research and production behind Google’s flagship products and AI/ML OSS offerings. The team advocates for the underlying design elements, developer platforms, components, and infrastructure at Google. These are the essential building blocks to drive the pace of innovation for ML developers.

As a Product Manager, you will lead teams developing libraries and tools for a wide variety of Machine Learning workloads including AI research, recommended systems, content understanding, and more. You will be working with wide product areas such as Search, Ads, YouTube, and more to power business critical products. Core ML’s mission is to Drive ML excellence for Google and ease the development of ML products for Google and all developers.

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 $168,000-$252,000 + 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

• Understand the workflows of internal and external machine learning experts from research and product development teams.
• Engage with all Google product areas (e.g., Ads, Search, YouTube, GCP, etc.) to understand their needs and build platform features to enable use cases.
• Drive strategy and roadmap development for machine learning stack tooling, and provide thought leadership on ML ecosystem strategy.
• Lead teams through defining, identifying, collecting, and tracking appropriate product or business metrics.
• Communicate with and influence executive leadership, engineering, and cross-functional teams to gain consensus and resources to deliver.