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Form of workMinimum qualifications:
- Bachelor's degree in Computer Science, Mathematics, or other relevant engineering discipline, or equivalent practical experience.
- 15 years of experience as a Software Engineering leader.
- Experience with technical innovation within cross-functional engineering environments.
Preferred qualifications:
- 15 years of experience as a Software Engineering leader in Infrastructure areas, and experience building ML infrastructure or products with ML usage.
- Experience building software runtimes or intermediate representations of programs in an ML environment.
- Experience successfully producing software products and large-scale distributed systems.
- Understanding of computing, data centers, enterprise software, and hardware infrastructure with technical knowledge to be credible with customers and engineers.
- Ability to balance detailed, technical guidance with big picture strategy, enabling teams to deliver products that are effective and creating ways to manage data.
- Excellent organization, prioritization, and written and verbal communication skills.
About the job
Core Machine Learning (ML) is the central machine learning platform team that provides ML software tools and hardware infrastructure to all the Google product areas, including Search, Ads, Youtube, Google Cloud, Maps, etc. Core ML is focused on Driving ML excellence for Google. Our aim is to simplify and make it easier to perform ML experimentation, development and productionization. We work closely with Google Research to bring new software and hardware research innovations to market. This enables us to better meet the challenge of the rapidly evolving hardware and software space around ML.
Foundations specifically focuses on enabling users with high performance, scalable, and portable infrastructure for a diverse set of hardware and ML frameworks. We build the capabilities that power Google's AI-first products, research, and cloud. As a member of ML Foundations, we have a unique mandate and opportunity to impact technical decisions and capabilities across the company.
Google Cloud accelerates organizations’ ability to digitally transform their business with the best infrastructure, platform, industry solutions and expertise. We deliver enterprise-grade solutions that leverage Google’s cutting-edge technology – all on the cleanest cloud in the industry. 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 $271,000-$399,000 + 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 for new hire 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
- Develop a strategic outlook for the low-level foundations of ML. Lead the design of APIs to support ML development and infrastructure that drives efficient execution and distribution of ML workloads across the ML fleet.
- Work with partners from ML frameworks (i.e., TensorFlow, JAX), Product Areas (i.e., Ads, Search, YouTube, Android), and hardware (i.e., CPU, GPU, TPU, Edge TPU) to develop APIs which support the full lifecycle of ML. Influence partners and stakeholders within and across the organization to build joint roadmaps and drive adoption of APIs.
- Influence external ML framework developer roadmaps via direct engagements as well as Operational Support Systems (OSS) strategy.
