Senior Software Engineer, Discover Feed Recommendations

Google•Mountain View, CA

14h•$174,000 - $252,000

About The Position

Google's software engineers develop technologies that help billions of users connect, explore, and interact with information. They work on products operating at massive scale and may contribute across areas such as information retrieval, distributed computing, large-scale system design, networking, data storage, security, artificial intelligence, natural language processing, UI design, and mobile. Engineers work on projects critical to Google's needs and may switch teams or projects as business needs evolve, while taking on problems across the full stack. Discover is Google's personalized interest feed, connecting users globally with content from across the web in real time. This role is focused on Discover User Modeling and Retrieval and its content exploration system, which addresses the challenge of newly ingested documents expiring before historical engagement provides enough signal to assess their quality. The system spans real-time, multi-tier lifecycle control and embedding-based cold-start retrieval. The role is part of Google Search AI, working at the intersection of large-scale systems and AI research, including models such as Gemini. The engineer will develop and launch content exploration and recommendation capabilities, with a focus on discovering new content and improving the freshness and efficiency of Discover's serving corpus.

Requirements

Bachelor's degree or equivalent practical experience.
5 years of experience with software development in one or more programming languages.
3 years of experience with end-to-end machine learning, such as model deployment, model evaluation, data processing, and debugging.
3 years of experience building and deploying recommendation system models in production, such as retrieval, prediction, ranking, personalization, search quality, or embeddings, and experience building architecture.
Experience developing personalization algorithms for user-specific content delivery.
Experience integrating generative AI tools or LLM interfaces into workflows.

Nice To Haves

Master's degree or PhD in Computer Science or a related technical field.
5 years of experience with data structures and algorithms.
Experience in Content Exploration/Exploitation, such as Bandit systems or Reinforcement Learning, or solving Cold Start problems.
Experience with feed recommendation systems or budgeting systems.
Experience with data pipelines and system design for real-time evaluation.

Responsibilities

Research and deploy machine learning models that identify content by combining multimodal LLM understanding, uncertainty estimation, and causal modeling to maximize exploration ROI at scale.
Drive projects from problem formulation and experimentation design through model training, real-time serving architecture, and production launches, collaborating with Feed Ranking, Content, and Infra teams.
Partner to align semantic applicant retrieval, ranking incentives, and warm-start handoffs so promising new content activates the organic recommendation flywheel.
Lead zero-history discovery for Discover's top formats, integrating dynamically generated AI content across the stack and surfacing breaking news within minutes of publication.
Evolve StarSearch into an intelligent gatekeeper for Discover's content ecosystem by bootstrapping fresh, niche, and creator supply, expanding personalization headroom, and pruning unengaged content to keep the serving corpus fresh and efficient.