Staff Software Engineer, AI/ML, Chrome Intelligence

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 manage information at a 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.

In this role, you will serve as an AI/ML Technical Lead for Chrome's AI features, particularly Gemini in Chrome. You will guide development of ML models and features with emphasis on safety and security, while leading engineers to enhance Chrome's agentic capabilities including autofill, tool invocation, Model Context Protocol (MCP) services, and browser automation, ensuring users remain safe and secure.ChromeOS delivers quality computing at scale to provide universal and unfettered access to information, entertainment, and tools. Our mission is to empower anyone to create and access information freely through fast, secure, simple, and intelligent computing.

The US base salary range for this full-time position is $197,000-$291,000 + 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 share 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 benefits at Google.

Responsibilities

• Design and train machine learning models (both GenAI and non-GenAI) to keep users safe and secure.
• Develop data pipelines including automated attack generation and running evaluations.
• Design and run live experiments, deploy models in production, analyze logs and adjust the models.
• Facilitate alignment and clarity across teams on goals, outcomes, and timelines while influencing and coaching a distributed team of engineers.
• Provide technical leadership on high-impact projects while managing project priorities, deadlines, and deliverables.

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 with one or more of the following: speech/audio (e.g., technology duplicating and responding to the human voice), reinforcement learning (e.g., sequential decision making), ML infrastructure, or specialization in another ML field.
• 5 years of experience with ML design and ML infrastructure (e.g., model deployment, model evaluation, data processing, debugging, fine tuning).

Preferred qualifications:

• Master’s degree or PhD in Engineering, Computer Science, or a related technical field.
• 8 years of experience with data structures and algorithms.
• 3 years of experience in a technical leadership role leading project teams and setting technical direction.
• 3 years of experience working in a complex, matrixed organization involving cross-functional, or cross-business projects.
  
• Understanding of feature engineering and analyzing data for building ML modes.
• Able to ideate, run, iterate, and analyze experiments while drawing conclusions from metrics and logs.