Software Engineer, Android AI

About the role

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 ML infrastructure (e.g., model deployment, model

evaluation, optimization, data processing, debugging).

• Experience with GenAI techniques (e.g., LLMs, Multi-Modal, Large Vision

Models) or with GenAI-related concepts (language modeling, computer vision).

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 or machine learning

research.

• Experience in Natural Language Processing, Large Language Models, and

Computer Vision.

• Proficiency in one of the following programming languages: Python, Kotlin, or

Java.

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 technology,

including advanced Machine Learning modeling with Large Language Models, and by

leveraging and improving personal context intelligence derived from connected

Google services. You will develop AI agents that effectively understand user

behavior, screen content, tools, and Application Programming Interfaces. You

will optimize Machine Learning (ML) models for on-device performance to build

private and personalized AI experiences.

Android is Google’s mobile operating system powering more than 3 billion devices

worldwide. Android is about bringing computing to everyone in the world. We

believe computing is a super power for good, enabling access to information,

economic opportunity, productivity, connectivity between friends and family and

more. We think everyone in the world should have access to the best computing

has to offer. We provide the platform for original equipment manufacturers

(OEMs) and developers to build compelling computing devices (smartphones,

tablets, TVs, wearables, etc) that run the best apps/services for everyone in

the world.Individual pay is determined by factors including job-related skills,

experience, and relevant education or training.

US: $147000 - $210000 (USD) + 15% bonus target + equity + benefits

Learn more about benefits at Google

[https://www.google.com/about/careers/applications/benefits/].

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, and advocate the adoption of new techniques

to solve issues.