Software Engineer III, AL/ML

### 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, optimization, data processing, debugging).

### Preferred qualifications:

• Master's degree or PhD in Computer Science or related technical fields.
• 2 years of experience with data structures or algorithms.
• Experience developing accessible technologies.
• Ability to perform feature engineering, analyze data for ML models development, and ideate, execute, and evaluate experiments.

About the job

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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.

As an Artificial Intelligence/Machine Learning (AI/ML) Software Engineer in the team you'll play a key role in improving Chrome's Agentic capabilities quality and building Gemini in Chrome features. Delivering a browser that's more assistive and agentic to its 4.2B+ users. 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 Software Engineers (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.

Responsibilities

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• 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 test evaluation datasets and autoraters to help us hill-climb and push the frontiers of what Gemini can do in Chrome.
• Run live experiments, deploying models in production, and using 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 is proud to be an equal opportunity workplace and is an affirmative action employer. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or Veteran status. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. See also Google's EEO Policy and EEO is the Law. If you have a disability or special need that requires accommodation, please let us know by completing our Accommodations for Applicants form.