Minimum Qualifications
Check you match the skill requirements for this role, as well as associated experience, then apply with your CV below.
- Bachelor's degree or equivalent practical experience.
- 8 years of experience in software development, with data structures / algorithms.
- 7 years of experience building and developing infrastructure, distributed systems, networks, or with compute technologies, storage, or hardware architecture.
- 5 years of experience with design and architecture, and testing / launching software products.
Preferred Qualifications
- Experience with system software, distributed systems, and multi-component software systems.
- Experience with the Linux kernel interface, accelerators (e.g., GPUs and TPUs), and containers.
- Experience with GPUs, TPUs, and Accelerators.
- Experience in developing and releasing system software products and C / C++ programming.
- Understanding of key concepts of performance analysis and tuning.
- Passion for reliability, efficiency, and scale.
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.
Responsibilities
- Design, implement, and analyze low-level computer systems, including accelerators (e.g., TPUs and GPUs), and their interactions with kernel and hardware.
- Collaborate with partner teams as well as users across Google, Machine Learning, Hardware Platform, SRE teams, and Google's internal / Cloud users.
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