Group Product Manager, Machine Learning Frameworks Applied Ecosystem

3 Months ago • 10-15 Years • Product Management • Artificial Intelligence • $214,000 PA - $305,000 PA

Job Summary

Job Description

At Google, we prioritize our users. To serve a constantly evolving world, we need Product Managers who are adaptable and passionate about developing products that impact millions daily. In this role, you'll collaborate cross-functionally to guide products from conception to launch, bridging the technical and business realms. You'll excel at breaking down complex problems into actionable steps for product development. One of the reasons Google consistently delivers innovative, world-changing products is our collaborative approach to Product Management. Our team closely works with creative engineers, designers, marketers, etc., to design and develop technologies that enhance access to global information. We guide products throughout the execution cycle, focusing on analyzing, positioning, packaging, promoting, and tailoring our solutions to our users. The team builds the tooling, service, and technical foundations to empower machine learning research and production behind Google's products and AI/ML OSS offerings. You'll lead teams developing ML Frameworks that enable developers to rapidly leverage models and innovation across internal and external AI ecosystems. You'll focus on Keras and collaborate with teams developing JAX, PyTorch, serving technologies, and more. You'll work extensively with both internal product areas and the external OSS community. Core ML's mission is to drive ML excellence for Google and the world. We simplify the development of ML products for Google and all developers, accelerating ML innovation from Google research and Google product areas to all of Google's products.
Must have:
  • Bachelor's degree or equivalent experience
  • 10 years of experience in product management or related technical roles
  • 5 years of experience taking technical products from conception to launch
  • Experience with Generative AI or Large Language Models
  • Experience with engineering
Good to have:
  • Master's degree in a technology or business-related field
  • 6 years of experience in full life-cycle product management and delivery
  • 3 years of experience with AI/ML model or tooling development (e.g., Product Management or Engineering)
Perks:
  • Bonus
  • Equity
  • Benefits

Job Details


Minimum qualifications:

  • Bachelor's degree or equivalent practical experience.
  • 10 years of experience in product management or related technical role.
  • 5 years of experience taking technical products from conception to launch.
  • Experience with the domain area of Generative AI or Large Language Models.

Preferred qualifications:

  • Master's degree in a technology or business related field.
  • 6 years of experience in full life-cycle product management and delivery.
  • 3 years of experience with AI/ML model or tooling development (e.g., Product Management or Engineering).
  • 3 years of experience with engineering.

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 team builds the tooling, service, and technical foundations to enable machine learning research and production behind Google’s products and AI/ML OSS offerings.

In this role, you will lead teams developing ML Frameworks that enable developers to rapidly take advantage of models and innovation happening across internal and external AI ecosystems. You will focus on Keras and will also interact with teams developing JAX, PyTorch, serving technologies, and more. You will work heavily with both internal product areas and also the external OSS community. Core ML’s mission is to drive ML excellence for Google and the world. We ease the development of ML products for Google and all developers. We accelerate ML innovation from Google research and Google product areas to all of Google’s products.

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 .

Responsibilities

  • Understand the workflows of internal and external applied ML Developers.
  • Engage with Google product areas and the wider community 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 and provide thought leadership on ML ecosystem strategy.

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