Group Product Manager, Machine Learning, Frameworks and Services
Sunnyvale, CA, USA; Seattle, WA, USA
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 building and shipping technical products.
Preferred qualifications:
- Master's degree in a technology or business related field.
- Experience building or using machine learning (ML) developer tools.
- Experience with Generative AI models.
- Experience influencing large-scale cross-functional decisions involving participating stakeholders.
- Experience with developer community growth and engagement.
- Understanding of both Server-side and On Device ML.
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 CoreML team builds the tooling, service, and technical foundations to enable machine learning research and production behind Google’s products and AI/ML offerings. We are owners and 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 machine learning (ML) developers. We look across Google’s products to build central solutions, break down technical barriers and strengthen existing systems. As the CoreML team, we have a mandate and a unique opportunity to impact important technical decisions across the company.
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 $214,000-$305,000 + 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
- Provide thought leadership on machine learning (ML) ecosystem strategy. Understand the workflows of internal and external machine learning experts from research and product development teams.
- Engage with all Google product areas (e.g., Google Deepmind, Ads, Search, YouTube, Google Cloud Platform, etc.) to understand their needs and build platform features to enable use cases.
- Drive strategy and roadmap development for machine learning stack tooling.
- 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 required resources to deliver.
Tags: Consulting CoreML Engineering GCP Generative AI Google Cloud Machine Learning Research
Perks/benefits: Career development Equity Salary bonus
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