Software Engineer, TPU Infrastructure, Google Cloud
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Minimum qualifications:
- Bachelor’s degree or equivalent practical experience.
- 2 years of experience in backend Infrastructure development.
- Experience in general purpose coding languages like C++, Go, or Python development.
- Experience with algorithms, data structures, software development, and distributed computing.
Preferred qualifications:
- Experience designing reliable, fault-tolerant and high performance distributed systems.
- Experience with building cloud based services ideally with GCP.
- Experience with large-scale distributed systems or Machine Learning (ML) systems (training and serving for computer vision, speech recognition, natural language processing, machine translation models).
- Experience with reliability, large-scale distributed systems, Go, Google Cloud Platform, tensor processing unit (TPU), and service level objectives.
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.
The TPU Infra team is the engine behind Google’s AI Hypercomputer, responsible for the technical strategy and execution of the Machine Learning (ML) Compute IaaS platforms.
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
- Design and build scalable software capabilities to manage the availability, scheduling, and reliability of the Cloud TPU Hypercomputer stack (VMs, Networking, Storage, GKE etc.).
- Architect infrastructure solutions to ensure industry-leading availability guarantees for large-scale training and inference workloads.
- Develop telemetry and tooling to establish service level objectives (SLO) and service level agreements (SLA), and to enable rapid debugging of complex infrastructure issues across the fleet.
- Collaborate with platform, hardware, networking, and SRE teams to scale and manage accelerator capacity, including new TPU generations, ensure a seamless experience for customers.
- Design and implement reliable ML infrastructure that enables training and serving cutting edge models at massive scale, troubleshoot complex distributed system issues across the stack (hardware, kernel, network), build the automation, tooling, and telemetry needed to turn operational findings into permanent software fixes and improved SLOs.
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