Senior Staff Software Engineer, Gemini

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, and 3 years

of experience with software design and architecture.

• 5 years of experience with one or more of the following: Speech/audio (e.g.,

technology duplicating and responding to the human voice), reinforcement

learning (e.g., sequential decision making), ML infrastructure, or

specialization in another ML field.

• 5 years of experience with ML design and ML infrastructure (e.g., model

deployment, model evaluation, data processing, debugging, fine tuning).

• Experience integrating generative AI tools or LLM interfaces into workflows.

PREFERRED QUALIFICATIONS:

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

technical field.

• 8 years of experience with data structures/algorithms.
• 3 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.

In this role, you will work on a large-scale distributed system that is critical

for the AI adoption for Google Cloud Platform (GCP). You will drive core infra

pieces (Autocloud Simulation and Benchmark, Quality Self-improvement, Agentic

Eval Workflow, GCP Quality Gate, Gemini Upstreaming, GCA Feature Store, etc.).

Your work is a combination of infra, quality, AI. Gemini Cloud Assist is

expanding rapidly as a very core foundation for GCP's AI initiative. You will

have the opportunity to influence and work across Google Cloud, DeepMind, and

the external AI ecosystem.

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.

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:

• Design, build, and scale large-scale distributed ML infrastructure and

tooling, including the Simulation and Benchmark platform, to support Gemini

post-training and accelerate GCP's AI adoption.

• Lead the development of advanced AI quality components, such as agentic

self-improvement, evaluation workflows, Gemini upstreaming, and automated

quality gates for first-party skills.

• Lead robust software design and automated testing practices, participate in

on-call rotations, and continuously optimize test and production environments

for reliability and performance.

• Coach and mentor junior and mid-level engineers, enforce architectural best

practices, and actively cultivate a high-performing team culture.