Senior Staff Software Engineer, AI/ML, Google Cloud

About the role

MINIMUM QUALIFICATIONS:

• Bachelor’s degree or equivalent practical experience.

• 8 years of experience in software development.
• 7 years of experience leading technical project strategy, ML design, and

optimizing industry-scale ML infrastructure (e.g., model deployment, model

evaluation, data processing, debugging, fine tuning).

• 5 years of experience with design and architecture; and testing/launching

software products.

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.
• 5 years of experience in a technical leadership role leading project teams

and setting technical direction.

• 3 years of experience working in a complex, matrixed organization involving

cross-functional, or cross-business projects.

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 Cloud GPU team is central to AI innovation, dedicated to building and

maintaining an industry-leading GPU fleet and AI Platform. Our core mission is

to empower Google Cloud's most sophisticated training and inference customers by

providing unparalleled computational resources. We're responsible for the

lifecycle of GPU offerings from the initial launch of new GPU families to ensure

their optimal reliability and operational excellence for AI workloads.

Our team grows at the intersection of hardware, software, data science and

applied AI, pushing the boundaries of what's possible in accelerated computing.

We collaborate closely with internal and external partners to deliver the

foundational infrastructure that fuels advancements in AI across industries.

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 team behind Google's groundbreaking innovations, empowering

the development of our 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: $262000 - $364000 (USD) + 25% bonus target + equity + benefits

Learn more about benefits at Google

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

RESPONSIBILITIES:

• Execute technical roadmaps for the GPU ecosystem, anticipating market shifts

to keep Google Cloud at the forefront of AI infrastructure.

• Collaborate with engineering teams to integrate new GPU architectures into

Google Compute Engine (GCE) for rapid workload availability.

• Oversee the lifecycle of accelerator solutions, guaranteeing consistent

performance and stability for user applications.

• Serve as a technical advocate during critical issues, collaborating directly

with customers to resolve challenges and translating their feedback into

platform enhancements.

• Design robust software solutions meeting the massive scalability and

performance requirements of Google Cloud’s global network.