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Job Details
Posted date: Jan 07, 2026
Location: Seattle, WA
Level: Senior
Estimated salary: $171,500
Range: $141,000 - $202,000
Description
Design and train machine learning models (both GenAI and non-GenAI). Employ a wide variety of approaches to improve the model such as prompt engineering, agent orchestration, and in some cases post-training. Contribute to creating testing eval datasets and autoraters to help us hill-climb and push the frontiers of what Gemini can do in Chrome. Run live experiments, deploy models in production, and use experimental results to improve model performance. Implement solutions in one or more specialized ML areas, utilize ML infrastructure, and contribute to model optimization and data processing.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.
As an AI/Machine Learning Software Engineer in the team, you will play a key role in improving Chrome's Agentic capabilities quality and building Gemini in Chrome features. You will have the opportunity to collaborate with many teams across Chrome and Google, delivering a various set of features and technologies to bring the full potential benefit of AI/ML to Chrome to help our users learn, create, and get things done on the web. You will have the opportunity to lead other SWEs on a range of problems inherent in ML model development, steering ML infra development, and enabling new features.The Platforms and Devices team encompasses Google's various computing software platforms across environments (desktop, mobile, applications), as well as our first-party devices and services that combine the best of Google AI, software, and hardware. Teams across this area research, design, and develop new technologies to make our user's interaction with computing faster and more seamless, building innovative experiences for our users around the world.
The US base salary range for this full-time position is $141,000-$202,000 + 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.
Qualifications
Minimum qualifications: Bachelor’s degree or equivalent practical experience. 2 years of experience with software development in one or more programming languages, or 1 year of experience with an advanced degree. 1 year 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. 1 year of experience with ML infrastructure (e.g., model deployment, model evaluation, data processing, debugging).Preferred qualifications: Master's degree or PhD in Computer Science or related technical fields. 2 years of experience with data structures and algorithms. Experience developing accessible technologies.
Extended Qualifications
Bachelor’s degree or equivalent practical experience. 2 years of experience with software development in one or more programming languages, or 1 year of experience with an advanced degree. 1 year 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. 1 year of experience with ML infrastructure (e.g., model deployment, model evaluation, data processing, debugging).Check out other jobs at Google.