Software Engineer, Generative AI, Shopping Product Graph, Commerce

About the role

MINIMUM QUALIFICATIONS:

• Bachelor’s degree or equivalent practical experience.

• 2 years of experience with software development in one or more programming

languages (e.g., C++, Python, or SQL), or 1 year of experience with an

advanced degree.

• 1 year of experience with ML infrastructure (e.g., model deployment, model

evaluation, optimization, data processing, debugging).

• Experience with GenAI techniques (e.g., LLMs, Multi-Modal, Large Vision

Models) or with GenAI-related concepts (language modeling, computer vision).

PREFERRED QUALIFICATIONS:

• Master's degree or PhD in Computer Science or related technical fields.

• 2 years of experience with data structures and algorithms.
• 1 year of experience building Generative AI Agents.
• 1 year of experience developing AI auto-raters and new agentic systems to

assess headroom and improve quality.

• Experience exploring new data sources from the web or merchants to improve

our ML model or product understanding performance.

• Experience developing accessible technologies.

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.

We're responsible for building this graph and attribute understanding for

billions of products and offers. Our team uses ML/AI to perform large-scale

clustering on product data and Large Language Model (LLM) inference to extract

key facts and features of those products. Our product modeling and understanding

powers key features across many surfaces—from generating product responses in AI

Mode on Search and improving the quality of new experiences in Ads, to helping

creators tag products in YouTube (YT).

People shop on Google more than a billion times a day - and the Commerce team is

responsible for building the experiences that serve these users. The mission for

Google Commerce is to be an essential part of the shopping journey for consumers

• from inspiration to to a simple and secure checkout experience - and the best

place for retailers/merchants to connect with consumers. We support and partner

with the commerce ecosystem, from large retailers to small local merchants, to

give them the tools, technology and scale to thrive in today’s digital

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

experience, and relevant education or training.

US: $147000 - $210000 (USD) + 15% bonus target + equity + benefits

Learn more about benefits at Google

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

RESPONSIBILITIES:

• Write product or system development code.

• Collaborate with peers and stakeholders through design and code reviews to

ensure best practices amongst available technologies (e.g., style guidelines,

checking code in, accuracy, testability, and efficiency).

• Contribute to existing documentation or educational content and adapt content

based on product/program updates and user feedback.

• Triage product or system issues and debug/track/resolve by analyzing the

sources of issues and the impact on hardware, network, or service operations

and quality.

• Implement GenAI solutions, utilize ML infrastructure, and contribute to data

preparation, optimization, and performance enhancements.