Staff Software Engineer, User AI Flywheel, Search Intelligence

Staff Software Engineer, User AI Flywheel, Search Intelligence corporate_fare Google place Mountain View, CA, USA bar_chart Advanced Advanced Experience owning outcomes and decision making, solving ambiguous problems and influencing stakeholders; deep expertise in domain.

Minimum qualifications:

Bachelor's degree or equivalent practical experience. 8 years of experience in software development. 5 years of experience testing, and launching software products, and 3 years of experience with software design and architecture. 5 years of experience leading ML design and optimizing ML infrastructure (e.g., model deployment, model evaluation, data processing, debugging, fine tuning). 2 years of experience with GenAI techniques (e.g., LLMs, Multimodal, Large Vision Models) or with GenAI-related concepts (language modeling, computer vision).

Preferred qualifications:

Master's degree or PhD in Engineering, Computer Science, or a related technical field. Experience in reinforcement learning with human feedback (RLHF) as applied to LLM modeling, data collection, and evaluation. Experience in fine-tuning and optimizing large language models, demonstrating a deep understanding of performance enhancement techniques. Understanding of ML systems and production infrastructure, enabling effective collaboration with engineers and establishing credibility with customers. Ability to seamlessly shift between providing detailed technical direction and contributing to the broader strategic outlook for LLM initiatives. Ability to successfully develop and implement technology solutions that deliver impact at scale. 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. With your technical expertise you will manage project priorities, deadlines, and deliverables. You will design, develop, test, deploy, maintain, and enhance software solutions. In Google Search, we're reimagining what it means to search for information - any way and anywhere. To do that, we need to solve complex engineering challenges and expand our infrastructure, while maintaining a universally accessible and useful experience that people around the world rely on. In joining the Search team, you'll have an opportunity to make an impact on billions of people globally. The US base salary range for this full-time position is $207,000-$300,000 + bonus + equity + benefits. Our salary ranges are determined by role, level, and location. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training. Your recruiter can more about the specific salary range for your preferred location during the hiring process. Please note that the compensation details listed in US role postings reflect the base salary only, and do not include bonus, equity, or benefits. Learn more about . Responsibilities Advocate the development of modeling, tuning and optimization techniques to enhance Large Language Model (LLM) performance, quality, and capabilities. Innovate in the design and implementation of user signals driven improvement of LLMs, to address known loss patterns and response quality behaviors and capabilities. Partner with experts from Google Research and DeepMind to advance LLM technologies and integrate them into groundbreaking products. Demonstrate exceptional teamwork, sharing your expertise in system design, machine learning modeling, and coding practices tailored to the LLM domain. Cultivate strong relationships with stakeholders across the organization to collaboratively define and execute LLM initiatives.