Minimum qualifications:
- Bachelor's degree in Computer Science or equivalent practical experience.
- Candidates will typically have 8 years of experience in software development, and with data structures/algorithms.
- Typically 5 years of experience testing, and launching software products, and 3 years of experience with software design and architecture.
- Experience with system design and software development in C, C++ or RUST.
- Master's degree or PhD in Engineering, Computer Science, or a related technical field.
- Experience with machine learning technologies (e.g. Tensorflow), developing and/or training models, or implementing solutions that evoke such models.
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About the job
Google's software engineers develop the next-generation technologies that change how billions of users connect, explore, and interact with information and one another. Our products need to handle information at massive scale, and extend well beyond web search. We're looking for engineers who bring fresh ideas from all areas, including information retrieval, distributed computing, large-scale system design, networking and data storage, security, artificial intelligence, natural language processing, UI design and mobile; the list goes on and is growing every day. As a software engineer, you will work on a specific project critical to Google's needs with opportunities to switch teams and projects as you and our fast-paced business grow and evolve. We need our engineers to be versatile, display leadership qualities and be enthusiastic to take on new problems across the full-stack as we continue to push technology forward.
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.
Responsibilities
- Measure and report the efficiency of the ML fleet, generate and collect metrics that help identify optimization opportunities, and drive improvements via changes to Core ML products and services.
- Measure and report the fleetwide adoption of Core ML products and services.
- Collect metrics to inform the ML software/hardware roadmap.
- Provide data driven actional feedback to ML job owners, product area resource planners, and Fleet resource planners.
- Engage with partner teams across the Core ML organization and key product areas. Work with PM, TPM and ML experts, as well as other SWEs, to understand ML telemetry needs, define and develop ML telemetry, and make them accessible to those working on ML metrics.