Software Engineer III, Managed AI/ML Infrastructure
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Minimum qualifications:
- Bachelor's degree in Computer Science, Math, a related technical field, or equivalent practical experience.
- 2 years of experience with data structures/algorithms and software development in one or more programming languages.
- Experience with one or more programming languages such as Java, Python, Go, JavaScript, C++ or similar.
- Experience in software design, problem solving and debugging.
Preferred qualifications:
- Experience in delivering cloud based products.
- Experience in building highly reliable systems.
- Familiarity with basic structures and principles of object-oriented programming.
About the job
Google Cloud's software engineers develop the next-generation technologies that change how billions of users connect, explore, and interact with information and one another. 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 Cloud's needs with opportunities to switch teams and projects as you and our fast-paced business grow and evolve. You will anticipate our customer needs and be empowered to act like an owner, take action and innovate. 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.
The GCE Managed Infrastructure organization contributes to the GCE Control Plane layer that manages Virtual Machines' lifecycle in Google Cloud Platform. We translate API calls that our users and clients make to GCE into operations orchestrated across multiple cloud services, delivering the machines and making sure their behavior follows demand, schedules and constraints. We also build Managed Instance Groups for running clusters of Virtual Machines (VMs) in a unified way, with capabilities like autohealing, autoscaling or auto-updating.
The MIG AI/ML Infrastructure team concentrates on supporting new accelerator (TPU, GPU) VM families and features in order to fulfill the massive computational needs of AI/ML workloads.
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
- Implement and maintain highly reliable, large-scale computer systems. Participate in analysis and design of solutions for managing orchestration and lifecycle of millions of Virtual Machines.
- Participate in complex and high-visibility projects supporting Google's TPU and GPU fleet and work and integrate with many stakeholders from across the Google Cloud Platform (GCP) stack (i.e., other GCE teams, GKE, Cloud TPU, Borg, etc.).
- Work and integrate with stakeholders from across the Google Cloud Platform stack.
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