The role
From Google's own posting.
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 .
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.
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.
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).