Product Manager II, Human Data Acquisition, AI Data

Minimum qualifications:

• Bachelor's degree or equivalent practical experience.
  
• 5 years of experience in product management or related technical role.
  
• 2 years of experience experience developing or launching infrastructure products or technologies within artificial intelligence, Machine Learning, networking, storage, compute hardware, databases, file systems, data analytics, cluster management, and other software infrastructure areas.
• 1 year of experience providing analysis insight.

Preferred qualifications:

• Master's degree in a technology or business related field.
  
• 3 years of experience in a role preparing and delivering technical presentations to senior leadership.

2 years of experience in software development or engineering, working cross-functionally with engineering, UX/UI, sales finance, and other stakeholders.

Experience building and launching new products in human data collection and building tooling or infrastructure.

Knowledge in product management, engineering, data science, and operations.

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 work closely with an Engineering team to best determine priorities, the product roadmap, define requirements, and keep your finger on the pulse of customer needs. You will be responsible for driving multiple projects forward, from inception to launch.

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

• Define strategy, direction, execution, and product requirements for new features by working closely with UX to deeply understand customer needs.
• Drive feature and release lifecycle working closely with Engineering and accelerate adoption by partnering closely with Operations across multiple product areas.
• Work with the Data Science team to ensure the platform is producing high-quality data, including defining data quality offerings.
• Stay aware of the third-party data acquisition market, understanding what the competition is doing, and ensuring our offerings are leading the market for our internal customers.
• Understand the challenges and opportunities associated with building critical tooling and infrastructure for developing the next generation of AI/ML models.