Join Google's innovative search intelligence team and contribute to the future of how billions connect with information. This role is central to developing cutting-edge technologies that redefine search experiences.

As a Staff Engineer, you'll tackle complex challenges in large-scale systems, artificial intelligence, and distributed computing. You'll have the unique opportunity to shape the evolution of personalization within Google Search and impact a global user base.

We seek versatile engineers with a passion for problem-solving and leadership qualities. You will be instrumental in driving technological advancements across the full stack, ensuring Google Search remains universally accessible and useful.

Lead the architectural evolution of personalization within Google Search, driving innovation in AI for this critical domain.

Develop and enhance software solutions using languages like Java, Kotlin, C++, and Python, focusing on model validation and development.

Collaborate with advanced systems and frameworks including Magi Response Server (MaRS), Gemini, Orbit/Nemo, and other internal AI tools.

Apply your expertise in AI fluency to solve complex problems with a high degree of ambiguity, contributing to the development of intelligent search functionalities.

A Bachelor's degree or equivalent practical experience is required.

Minimum of 5 years of experience is expected in areas such as Speech/Audio technology, Reinforcement Learning, ML infrastructure, or specialized Machine Learning fields.

Possess 5 years of experience in leading ML design and optimizing ML infrastructure, covering aspects like model deployment, evaluation, and data processing.

Demonstrate 5 years of experience in testing and launching software products, alongside 3 years of experience in software design and architecture.

Familiarity with integrating generative AI tools or Large Language Model (LLM) interfaces into workflows is essential.

Preferred qualifications include a Master's degree or PhD, 8 years of experience with data structures and algorithms, and experience with agentic frameworks and LLM-powered automation.