Senior Product Manager, On-Device Machine Learning, Developer Pillar Full-time

Minimum qualifications:

• Bachelor’s degree or equivalent practical experience.
• 8 years of experience in product management or a related technical role.
• 3 years of experience taking technical products from conception to launch.
• Experience developing or launching infrastructure products or technologies within networking, storage, compute hardware, databases, file systems, data analytics, cluster management, and other software infrastructure areas.

Preferred qualifications:

• Master’s degree in a technology or business related field.
• 10 years of experience in product management, with a focus on developer tools or AI/ML.
• Experience taking a product from 0 to 1 and from 1 to 10.
• Excellent problem-solving skills, with the ability to translate complex technical concepts into clear product requirements.
• Excellent communication, people management, and presentation skills.

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.

Core Machine Learning (ML) mission is to drive ML excellence for Google and the World. This means building more reliable, easy to use, and flexible tools for ML practitioners so that our customers can more easily experiment with new research ideas and deploy them at scale in production. This means building easy to use, trustworthy, and privacy preserving solutions for consumers of ML products. We aim to enable rapid innovation and adoption of machine learning across products built by Google and by Google Cloud customers.

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

• Gather requirements and define experiences that span the full software development lifecycle for various On-Device ML (ODML) initiatives across developer tools, driven by a deep understanding of market trends and current customer needs, and anticipate how those customer needs for edge computing will evolve over the next 3-5 years.
• Partner with Developer Relations and User Experience Researcher (UXR) and drive user interviews to deeply understand the user needs and requirements.
• Partner with engineering and product leaders within Core ML ODML teams and across organizational boundaries to help define and execute roadmaps, Product Requirements Documents (PRDs) and Objectives and Key Results (OKRs).
• Lead prioritized execution with a strong focus on customer needs, business outcomes, and success metrics.