Software Engineer, Android AI, Core

1 Month ago • 2 Years + • Mobile Development

Job Summary

Job Description

This Software Engineer role at Google focuses on Android AI Core development. Responsibilities include integrating a new native runtime from a chipmaker, assisting a third-party OEM with AI Core integration, collaborating with a product team on a GenAI feature (developing APIs, configuration, distribution, and troubleshooting), building a content safety evaluation pipeline, and setting up and monitoring infrastructure. The ideal candidate will have experience with Android application development, Java, and Android frameworks, and familiarity with data structures and algorithms. The role is crucial for improving Google's mobile products and services.
Must have:
  • Android app development experience
  • Java and Android framework expertise
  • Data structures and algorithms knowledge
  • Integration of new runtimes
  • API development and troubleshooting
  • Content safety pipeline creation
Good to have:
  • Experience in operability, reliability, or release engineering

Job Details

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.
  • 2 years of experience with data structures or algorithms in either an academic or industry setting.
  • 2 years of experience with Android application development.
  • Experience in Java and working with Android frameworks.

Preferred qualifications:

  • Experience in operability, reliability, or release engineering.

About the job

Mobile technology has been at the forefront of innovation, and the pace of development in this domain has never been greater. Google is committed to bringing amazing experiences to our mobile users. As a Software Engineer, Tools and Infrastructure, you will be at the heart of Google’s engineering process building software that empowers engineering teams to develop and deliver high quality mobile apps and services. We are focused on solving the hardest, most interesting challenges of developing software at scale without sacrificing stability, quality, velocity or code health.

We ensure Google's success by partnering with engineering teams and developing scalable tools and infrastructure that help engineers develop, test, debug and release software quickly. We impact thousands of Googlers and billions of users by increasing the pace of product development and ensuring our products are thoroughly tested. We are advocates for code health, testability, maintainability and best practices for development and testing.

Having access to all of Google's platforms and vast compute resources provides a unique opportunity to grow as an engineer. We typically work in small, nimble teams that collaborate on common problems across products and focus areas. As a result, the exposure to this broad set of problems provides diverse technical challenges as well as accelerated career growth.

Android is Google’s open-source 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.

Responsibilities

  • Integrate a new native runtime coming from a chipmaker and assist a Third Party OEM in including AI Core in one of their upcoming phone launches.
  • Coordinate with a product team who is building an Generative Artificial Intelligence (GenAI) feature on top of AI Core by adding new Application programming interface (APIs), assisting with their feature configuration and distribution and troubleshooting them through development.
  • Build a content safety evaluation pipeline that will run thousands of adversarial examples through the on-device service so a Trust and Safety team can assess the safety of a GenAI feature.
  • Set up experiments and monitor infrastructure for functionality, performance, system health.

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