Google

Staff Software Engineer, Applied Research, Foundation User Models at Google. This role focuses on defining and executing the applied research roadmap for Large User Models, translating business goals into technical formulations, optimizing model performance with adaptation techniques, driving architectural improvements by influencing pre-training teams, and productionizing fine-tuning pipelines for recommendation engines. The role requires experience with Transformer-based models and ML design, with a focus on balancing quality output with strict inference latency requirements.

Staff Software Engineer focused on the User AI Flywheel for Google Search, aiming to enhance LLM performance, quality, and capabilities through user signals and advanced modeling techniques. The role involves innovating on LLM improvements, partnering with research teams, and integrating LLM technologies into products. Responsibilities include advocating for modeling/tuning/optimization, designing user signal-driven improvements, collaborating with research, and demonstrating expertise in system design, ML modeling, and coding for LLMs. The role requires experience in software development, ML design, ML infrastructure optimization, and GenAI techniques, with preferred experience in RLHF, fine-tuning, and ML systems production.