Bachelor's degree or equivalent practical experience.
8 years of experience in product management or related technical role.
3 years of experience developing or launching products or technologies within Artificial Intelligence or Machine Learning (AI or ML).
Preferred qualifications:
Master's degree in a technology or business related field.
5 years of experience in full life-cycle product management and delivery.
3 years of experience in engineering.
3 years of experience with AI/ML models or tooling development (Product Management or 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 Core ML’s mission is to drive Machine Learning (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.
As a Product Manager in CoreML within ML Frameworks, you will lead teams developing ML Frameworks and tooling that enable developers to take advantage of models and innovation happening across Artificial Intelligence (AI) ecosystems. In this role, you will focus on ensuring that internal ML developers have seamless access to innovation happening anywhere in the external ecosystem. You will work with internal Product Analysts (PAs) and also the external Open-Source Software (OSS) community.
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 $183,000-$271,000 + bonus + equity + benefits. Our salary ranges are determined by role, level, and location. 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 and tooling ecosystem of internal and external ML Developers.
Engage with Google product areas and research to understand their needs for engaging with external innovation.
Drive strategy and roadmap development for machine learning stack tooling.
Provide leadership on ML ecosystem strategy.
Lead teams through defining, identifying, collecting, and tracking product or business metrics.
Google
Google LLC started as a PhD project by Larry Page and Sergey Brin in 1998 at Stanford University. Google LLC has blossomed into a behemoth of the tech world. With its mission to organize the world's information and make it universally accessible and useful, Google’s search engine is its crown jewel. Online advertising, via AdWords and AdSense, forms the backbone of its financial success. Beyond search, Google has ventured into cloud computing, hardware, and software development. The innovative PageRank algorithm revolutionized search engine technology, and surviving the dot-com bubble burst and going public in 2004 spurred its meteoric growth. Acquiring YouTube stands as a testament to Google’s strategic expansion.