Software Engineer II, Shopping Core Ranking

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 are building a next-generation, AI-first ranking stack, leveraging Large Language Models (LLMs) like Gemini to power everything from training data generation to the core ranking algorithms served to billions of users across Search, the Shopping Tab, Product Viewers, and AI surfaces like AIM and GeminiApp.

Our mission is to deliver the highest quality, most relevant, and trustworthy product and offer rankings. We are moving beyond traditional ranking models to create a more intelligent, context-aware, and explainable system. In this role, you will help shape the future of e-commerce search quality by applying machine learning techniques at a massive scale, contributing to an end-to-end differentiable shopping quality stack.

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.

Responsibilities

• Design, develop, and ensure the reliability, performance, and quality of our LLM-based ranking models, including custom Gemini Encoder-Heavy models and prompted vanilla Gemini models.
• Improve model architecture, features, and training objectives to enhance products and offer ranking.
• Maintain and enhance our Gemini-based autoraters used for generating nuanced training data labels (e.g., relevance, quality).
• Manage, optimize, and develop complex Tflex data pipelines that feed into the model training process. Develop and improve automation for the entire model lifecycle, including training, validation, export, and deployment.
• Design, run, and analyze large-scale live experiments using Mendel to validate changes and understand user impact.

Minimum qualifications:

• Bachelor’s degree or equivalent practical experience.
• 1 year of experience with software development in one or more programming languages (e.g., Python, C, C++, Java, JavaScript).
• 1 year of experience with data structures and algorithms.
• 1 year of experience implementing core ML concepts.

Preferred qualifications:

• Experience with MLOps practices, including model versioning, deployment, and monitoring.
• Experience in programming languages used in machine learning and data engineering (Python, C++).
• Familiarity with search evaluation and live experiment frameworks (e.g., Mendel).
• Understanding of large language models, deep learning, and machine learning principles, especially as applied to ranking.
• Expertise in building, maintaining, and optimizing large-scale data processing and machine learning pipelines (e.g., Tflex, Beam).