Staff Software Engineer, Core Systems and Capacity Assurance

About the role

MINIMUM QUALIFICATIONS:

• Bachelor's degree or equivalent practical experience.

• 8 years of experience in software development.

• 5 years of experience testing, and launching software products.

• Experience integrating generative AI tools or LLM interfaces into workflows.
• Experience in data analysis, test automation, failure analysis and embedded

systems.

PREFERRED QUALIFICATIONS:

• Master’s degree or PhD in Engineering, Computer Science, or a related

technical field.

• 8 years of experience with data structures and algorithms.
• Experience in data center systems, linux, data center networking, machine

automation, ML hardware, and strong debugging and technical troubleshooting

skills.

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 Core Systems and Capacity Assurance (CSCA) Team is responsible for the

journey of a new system from the point of manufacturing to data center delivery.

We do this on projects that push the limits of technologies and provide you with

an opportunity to make a broad impact across all of Google's product families.

The technologies include systems that support machine learning, video

transcoding, security, general compute, image processing, and storage. You will

be a part of the new emerging technologies and systems that push the limits of

computation. Please note this position requires about 20% Travel to Google Data

Centers primarily in US, and also to Manufacturing CM partner sites in US,

Mexico, and possibly Asia.

The AI and Infrastructure team is redefining what’s possible. We empower Google

customers with breakthrough capabilities and insights by delivering AI and

Infrastructure at unparalleled scale, efficiency, reliability and velocity. Our

customers include Googlers, Google Cloud customers, and billions of Google users

worldwide.

We're the driving force behind Google's groundbreaking innovations, empowering

the development of our cutting-edge AI models, delivering unparalleled computing

power to global services, and providing the essential platforms that enable

developers to build the future. From software to hardware our teams are shaping

the future of world-leading hyperscale computing, with key teams working on the

development of our TPUs, Vertex AI for Google Cloud, Google Global Networking,

Data Center operations, systems research, and much more.

Individual pay is determined by factors including job-related skills,

experience, and relevant education or training.

US: $207000 - $300000 (USD) + 20% bonus target + equity + benefits

Learn more about benefits at Google

[https://www.google.com/about/careers/applications/benefits/].

RESPONSIBILITIES:

• Manage the development of automation, processes, and diagnostics in support

of new product introduction to enable the efficient installation,

configuration, testing and management of new data center hardware  from the

time of manufacturing to installation.

• Develop new product test solutions, and will work closely with our hardware

and software partner teams to ensure that the end to end data center

automated diagnosis and repair systems are working efficiently and integrated

properly with the signals generated from our test infrastructure and

diagnostics.

• Develop software that executes in thousands of systems in parallel and

develop the data insights required to analyze the complex result sets, and

optimize repair strategies for fault coverage and fault isolation.

• Manage the new product introduction process to ensure that new hardware

platforms turn up from manufacturing to our data centers.