About the job

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.

Our team is pioneering the future of Android by infusing the Operating System with intelligent, agentic capabilities. We utilize Large Language Models and other machine learning technologies to redefine the mobile experience.

In this role, you will have the opportunity to solve problems with the technology, including Advanced Machine Learning modeling with Large Language Models. Leveraging and improving personal context intelligence derived from connected Google services. You will develop AI agents that effectively understand user behavior, screen content and use tools, Application Programming Interfaces. You will optimize Machine Learning (ML) models for on-device performance, build private and personalized AI experiences.

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 $147,000-$211,000 + 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, build, and optimize the end-to-end machine learning systems and models that power android's next-generation AI agent. Translate ambiguous user needs and product goals for agentic AI into well-defined technical problems and Machine Learning (ML) solutions.

• Architect and implement data pipelines for collecting, cleaning, and processing the massive datasets required for training and fine-tuning ML models.

• Lead core machine learning model development and optimization, prioritizing on-device performance and user privacy. Establish evaluation frameworks to ensure AI features are reliable, helpful, and personalized.

• Collaborate closely with engineers, researchers, and product managers to integrate ML models and agentic capabilities into the Android ecosystem.

• Stay at the forefront of advancements in Large Language Models, AI agents, and on-device machine learning, advocate the adoption of new techniques to solve issues.

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 (Python)

• 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 a related technical field.

• 2 years of experience with data structures and algorithms.

• 2 years of experience in applied machine learning and research.

• Experience developing accessible technologies.

• Experience in Natural Language Processing, Large Language Models, and Computer Vision.