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 Discover Feed Recommendation team leads by recommending AI-generated content (AIGC) to fulfill user interests.
Responsibilities
Build advanced AI-generated content (AIGC) quality frameworks and agentic flows to generate content for proactive surfaces like Discover and Notifications.\nDevelop AI-generated content through advanced context engineering and agentic feedback loops to identify and deliver engaging stories globally.\nConduct advanced quality evaluations and leverage downstream dense recommendation signals and feedback to improve the performance of the AIGC stack.\nResolve key system-level bottlenecks in recommending and serving AIGC content to optimize efficiency for low-latency surfaces.\nNavigate high ambiguity, drive technical innovation for AIGC quality, and influence the broader organizational machine learning strategy.
Qualifications
Minimum
Bachelor’s degree or equivalent practical experience.\n8 years of experience in software development.\n5 years of experience in machine learning, recommendation systems, natural language processing, or a related field.\nExperience building offline and online quality evaluation frameworks for Large Language Models (e.g., LLM-as-a-judge, RLHF, DPO).\nExperience integrating generative AI tools or LLM interfaces into workflows.
Preferred
Master’s degree or PhD in Engineering, Computer Science, or a related technical field.\n8 years of experience with data structures/algorithms.\n3 years of experience in a technical leadership role leading project teams and setting technical direction.\nExperience optimizing machine learning inference, resolving system-level bottlenecks, and improving serving efficiency for low-latency global surfaces.\nExperience integrating large language model quality evaluation frameworks with downstream recommendation signals.